Wind Bias Research Articles

Ocean–atmosphere processes driving Indian summer monsoon biases in CFSv2 hindcasts

This paper analyzes the role of the Indian Ocean (IO) and the atmosphere biases in generating and sustaining large-scale precipitation biases over Central India (CI) during the Indian summer monsoon (ISM) in the climate forecast system version 2 (CFSv2) hindcasts that are produced by initializing the system each month from January 1982 to March 2011. The CFSv2 hindcasts are characterized by a systematic dry monsoon bias over CI that deteriorate with forecast lead-times and coexist with a wet bias in the tropical IO suggesting a large-scale interplay between coupled ocean–atmosphere and land biases. The biases evolving from spring-initialized forecasts are analyzed in detail to understand the evolution of summer biases. The northward migration of the Inter Tropical Convergence Zone (ITCZ) that typically crosses the equator in the IO sector during April in nature is delayed in the hindcasts when the forecast system is initialized in early spring. Our analyses show that the delay in the ITCZ coexists with wind and SST biases and the associated processes project onto the seasonal evolution of the coupled ocean–atmosphere features. This delay in conjunction with the SST and the wind biases during late spring and early summer contributes to excessive precipitation over the ocean and leading to a deficit in rainfall over CI throughout the summer. Attribution of bias to a specific component in a coupled forecast system is particularly challenging as seemingly independent biases from one component affect the other components or are affected by their feedbacks. In the spring-initialized forecasts, the buildup of deeper thermocline in association with warmer SSTs due to the enhanced Ekman pumping in the southwest IO inhibits the otherwise typical northward propagation of ITCZ in the month of April. Beyond this deficiency in the forecasts, two key ocean–atmosphere coupled mechanisms are identified; one in the Arabian Sea, where a positive windstress curl bias in conjunction with warmer SSTs lead to a weakening of Findlater jet and the other in the east equatorial IO where a remote forcing by the predominantly westerly bias in the western-central equatorial IO in the summer strengthen the seasonal downwelling Kelvin wave that in turn deepens the thermocline in the eastern IO. The equatorial Kelvin wave continues as a coastal Kelvin wave and disperses as Rossby waves off Sumatra and induces positive SST and precipitation biases in the eastern and southern Bay of Bengal. This study shows that the biases that first appear in winds lead to a cascade of coupled processes that exacerbate the subsequent biases by modulating the evolution of seasonal processes such as the annual Kelvin and Rossby waves and the cross-equatorial vertically integrated moisture transport. While this analysis does not offer any particular insights into improving the ISM forecasts, it is a foundational first step towards this goal.

Contributions of the atmosphere–land and ocean–sea ice model components to the tropical Atlantic SST bias in CESM1

In order to identify and quantify intrinsic errors in the atmosphere–land and ocean–sea ice model components of the Community Earth System Model version 1 (CESM1) and their contributions to the tropical Atlantic sea surface temperature (SST) bias in CESM1, we propose a new method of diagnosis and apply it to a set of CESM1 simulations. Our analyses of the model simulations indicate that both the atmosphere–land and ocean–sea ice model components of CESM1 contain large errors in the tropical Atlantic. When the two model components are fully coupled, the intrinsic errors in the two components emerge quickly within a year with strong seasonality in their growth rates. In particular, the ocean–sea ice model contributes significantly in forcing the eastern equatorial Atlantic warm SST bias in early boreal summer. Further analysis shows that the upper thermocline water underneath the eastern equatorial Atlantic surface mixed layer is too warm in a stand-alone ocean–sea ice simulation of CESM1 forced with observed surface flux fields, suggesting that the mixed layer cooling associated with the entrainment of upper thermocline water is too weak in early boreal summer. Therefore, although we acknowledge the potential importance of the westerly wind bias in the western equatorial Atlantic and the low-level stratus cloud bias in the southeastern tropical Atlantic, both of which originate from the atmosphere–land model, we emphasize here that solving those problems in the atmosphere–land model alone does not resolve the equatorial Atlantic warm bias in CESM1.

Evaluation of Wind Forecasts and Observation Impacts from Variational and Ensemble Data Assimilation for Wind Energy Applications

Abstract The U.S. Department of Energy Wind Forecast Improvement Project (WFIP) has recently been completed with the aim of 1) understanding the performance of different mesoscale data assimilation systems for lower-atmospheric wind prediction and 2) determining the observation impacts on wind forecasts within the different assimilation systems. Here an ensemble Kalman filter (EnKF) was tested against a three-dimensional variational data assimilation (3DVAR) technique. Forecasts lasting 24 hours were produced for a month-long period to determine the day-to-day performance of each system, as well as over 10 individual wind ramp cases. The observation impacts from surface mesonet and profiler/sodar wind observations aloft were also tested in each system for both the month-long run and the ramp forecasts. It was found that EnKF forecasts verified over a domain including Texas and Oklahoma were better than those of 3DVAR for the month-long experiment throughout the forecast window, presumably from the use of flow-dependent covariances in the EnKF. The assimilation of mesonet data improved both EnKF and 3DVAR early forecasts, but sodar/profiler data showed a degradation (EnKF) or had no effect (3DVAR), with the degradation apparently resulting from a lower-atmospheric wind bias. For the wind ramp forecasts, ensemble averaging appears to overwhelm any improvements flow-dependent assimilation may have on ramp forecasts, leading to better 3DVAR ramp prediction. This suggests that best member techniques within the EnKF may be necessary for improved performance over 3DVAR for forecasts of sharp features such as wind ramps. Observation impacts from mesonet and profiler/sodar observations generally improved EnKF ramp forecasts, but either had little effect on or degraded 3DVAR forecasts.

Impact of upper ocean processes and air-sea fluxes on seasonal SST biases over the tropical Indian Ocean in the NCEP Climate Forecasting System

The present study aims to examine the role of air–sea interactions and upper ocean processes in determining the tropical Indian Ocean (TIO) seasonal sea surface temperature (SST) bias in Climate Forecast System version 1 (CFSv1) and version 2 (CFSv2) free runs. CFSv1 displayed dipole like east–west SST bias over the equatorial Indian Ocean from boreal summer to winter and is consistent with errors (bias) in surface winds and upper ocean advection. Large zonal gradients in sea level pressure (SLP) bias and the associated surface wind biases are primarily responsible for the upper ocean current bias. However, over the southern Indian Ocean and parts of Arabian Sea, strong bias in heat flux and mixed layer depth (MLD) have mainly contributed for the SST biases in CFSv1. Equatorial current system is better represented in CFSv2 compared to CFSv1. Improvement in the representation of land-surface processes appears to be contributing towards improving atmospheric circulation and SLP gradients in CFSv2, which may be responsible for the improved ocean circulation. Importantly, east–west dipole like SST bias prevalent in CFSv1 is absent in CFSv2. However, there is a prominent systematic basin-wide TIO cold SST bias in CFSv2. Large biases in surface heat flux (net negative bias) and MLD (deeper) are mainly responsible for SST biases in CFSv2. Negative net heat flux bias in CFSv2 is primarily due to specific humidity bias-induced excess latent heat flux (LHF). Deepening of MLD is mainly due to strong convective mixing, a resultant of anomalous LHF release, which in turn leads to negative SST bias. Models comparison reveals that although representation of SST in CFSv2 is better than in CFSv1, it is essential to improve further the equatorial ocean dynamics and off-equatorial thermodynamics in the form of moist processes and radiative parameterization in order to reduce SST bias in CFSv2.

Climate Model Errors over the South Indian Ocean Thermocline Dome and Their Effect on the Basin Mode of Interannual Variability

AbstractAn open-ocean thermocline dome south of the equator is a striking feature of the Indian Ocean (IO) as a result of equatorial westerly winds. Over the thermocline dome, the El Niño–forced Rossby waves help sustain the IO basin (IOB) mode and offer climate predictability for the IO and surrounding countries. This study shows that a common equatorial easterly wind bias, by forcing a westward-propagating downwelling Rossby wave in the southern IO, induces too deep a thermocline dome over the southwestern IO (SWIO) in state-of-the-art climate models. Such a deep SWIO thermocline weakens the influence of subsurface variability on sea surface temperature (SST), reducing the IOB amplitude and possibly limiting the models’ skill of regional climate prediction. To the extent that the equatorial easterly wind bias originates from errors of the South Asian summer monsoon, improving the monsoon simulation can lead to substantial improvements in simulating and predicting interannual variability in the IO.

Monsoon-Induced Biases of Climate Models over the Tropical Indian Ocean

AbstractLong-standing biases of climate models limit the skills of climate prediction and projection. Overlooked are tropical Indian Ocean (IO) errors. Based on the phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble, the present study identifies a common error pattern in climate models that resembles the IO dipole (IOD) mode of interannual variability in nature, with a strong equatorial easterly wind bias during boreal autumn accompanied by physically consistent biases in precipitation, sea surface temperature (SST), and subsurface ocean temperature. The analyses show that such IOD-like biases can be traced back to errors in the South Asian summer monsoon. A southwest summer monsoon that is too weak over the Arabian Sea generates a warm SST bias over the western equatorial IO. In boreal autumn, Bjerknes feedback helps amplify the error into an IOD-like bias pattern in wind, precipitation, SST, and subsurface ocean temperature. Such mean state biases result in an interannual IOD variability that is too strong. Most models project an IOD-like future change for the boreal autumn mean state in the global warming scenario, which would result in more frequent occurrences of extreme positive IOD events in the future with important consequences to Indonesia and East Africa. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) characterizes this future IOD-like projection in the mean state as robust based on consistency among models, but the authors’ results cast doubts on this conclusion since models with larger IOD amplitude biases tend to produce stronger IOD-like projected changes in the future.

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC hmF2 data under geomagnetically quiet conditions

AbstractThis study demonstrates the usage of a data assimilation procedure, which ingests the FORMOSAT‐3/COSMIC (F3/C) hmF2 observations to correct the model wind biases to enhance the capability of the new global Ionosphere Plasmasphere Electrodynamics (IPE) model under geomagnetically quiet conditions. The IPE model is built upon the field line interhemispheric plasma model with a realistic geomagnetic field model and empirical model drivers. The hmF2 observed by the F3/C radio occultation technique is utilized to adjust global thermospheric field‐aligned neutral winds (i.e., a component of the thermospheric neutral wind parallel to the magnetic field) at midlatitudes according to a linear relationship between time differentials of the field‐aligned wind and hmF2. The adjusted winds are further applied to drive the IPE model. The comparison of the modeled electron density with the observations of F3/C and ground‐based GPS receivers at the 2012 March equinox suggests that the modeled electron density can be significantly improved in the midlatitude regions of the Southern Hemisphere, if the wind correction scheme is applied. Moreover, the F3/C observation, the IPE model, and the wind bias correction scheme are applied to study the 2012 Southern Hemisphere Midlatitude Summer Nighttime Anomaly (southern MSNA)/Weddell Sea Anomaly (WSA) event at December solstice for examining the role of the neutral winds in controlling the longitudinal variation of the southern MSNA/WSA behavior. With the help of the wind bias correction scheme, the IPE model better tracks the F3/C‐observed eastward movement of the southern MSNA/WSA feature. The apparent eastward movement of the southern MSNA/WSA features in the local time coordinate is primarily caused by the longitudinal variation in the declination angle of the geomagnetic field that controls the field‐aligned projection of both geographic meridional and zonal components of the neutral wind. Both the IPE simulations and the F3/C observations show the significant longitudinal variation in the speed of the eastward movement of the southern MSNA/WSA.

Processes Leading to Double Intertropical Convergence Zone Bias in CESM1/CAM5

Abstract The double intertropical convergence zone (ITCZ) bias in the eastern Pacific in the Community Earth System Model version 1 with Community Atmosphere Model version 5 (CESM1/CAM5) is diagnosed. In CAM5 standalone, the northern ITCZ is associated with inertial instability and the southern ITCZ is thermally forced. After air–sea coupling, the processes on both hemispheres are switched because the spatial pattern of sea surface temperature (SST) is changed. Biases occur during boreal spring in both CAM5 and the ocean model. In CAM5 alone, weaker-than-observed equatorial easterly in the tropical eastern South Pacific leads to weaker evaporation and an increase in local SST. The shallow meridional circulation overly converges in the same region in the CAM5 standalone simulation, the planetary boundary layer and middle troposphere are too humid, and the large-scale subsidence is too weak at the middle levels. These biases may result from excessive shallow convection behavior in CAM5. The extra moisture would then fuel stronger convection and a higher precipitation rate in the southeastern Pacific. In the ocean model, the South Equatorial Current is underestimated and the North Equatorial Countercurrent is located too close to the equator, causing a warm SST bias in the southeastern Pacific and a cold bias in the northeastern Pacific. These SST biases feed back to the atmosphere and further influence convection and the surface wind biases in the coupled simulation. When the convection in the tropical northeastern Pacific becomes thermally forced after coupling, the northern ITCZ is diminished due to colder SST, forming the so-called alternating ITCZ bias.

Mitigation of ECMWF–scatterometer wind biases in view of storm surge applications in the Adriatic Sea

The Adriatic Sea, a semi-enclosed sea extending about 900km by 200km and entirely surrounded by mountain chains, is subjected to high water levels produced essentially by the wind blowing along its major axis (sirocco). The operational storm surge models use the forecast fields produced by ECMWF atmospheric model as meteorological forcing. Recent works showed that in small basins surrounded by steep orography the ECMWF model underestimates the wind. This may introduce inaccuracies in forecasting the water level. Experiments conducted in the framework of the “Storm Surge for Venice” (eSurge-Venice) project, funded by the European Space Agency Data User Element program, were aimed to improve the operational forecasting of storm surge in the Northern Adriatic Sea by using satellite observations.The paper presents a methodology aimed to mitigate the ECMWF model underestimate of the sea surface wind by a tuning procedure based on the scatterometer-model wind speed and direction biases. The mitigation takes into account the spatial characteristics of the biases and is time dependent. This method globally reduces the model underestimate of the surface wind, handling the different areas of the basin differently, according to the spatial structure of the bias. The methodology is applied and verified over thirty-three test cases. It may be considered a tool to improve the present high water level forecast, waiting for the advent of convincing methodologies for scatterometer wind assimilation into the regional atmospheric models.

Simulations of the West African Monsoon with a Superparameterized Climate Model. Part I: The Seasonal Cycle

Abstract The West African monsoon seasonal cycle is simulated with two coupled general circulation models: the Community Climate System Model (CCSM), which uses traditional convective parameterizations, and the “superparameterized” CCSM (SP-CCSM), in which the atmospheric parameterizations have been replaced with an embedded cloud-resolving model. Compared to CCSM, SP-CCSM better represents the magnitude and spatial patterns of summer monsoon precipitation over West Africa. Most importantly, the region of maximum precipitation is shifted from the Gulf of Guinea in CCSM (not realistic) to over the continent in SP-CCSM. SP-CCSM also develops its own biases—namely, excessive rainfall along the Guinean coast in summer. Biases in rainfall from both models are linked to a misrepresentation of the equatorial Atlantic cold tongue. Warm sea surface temperature (SST) biases are linked to westerly trade wind biases and convection within the intertropical convergence zone. Improved SST biases in SP-CCSM are linked to increased tropospheric warming associated with convection. A weaker-than-observed Saharan heat low is found in both models, which explains why the main band of precipitation does not penetrate as far northward as observed. The latitude–height position of the African easterly jet (AEJ) is comparable to observations in both models, but the meridional temperature and moisture gradients and the strength of the jet are too weak in SP-CCSM and too strong in CCSM. Differences in the AEJ are hypothesized to be influenced by the contrasting representation of African easterly waves in both models; no wave activity is found in CCSM, and strong waves are found in SP-CCSM.

Orographic Wave Drag over the Southern Ocean: A Linear Theory Perspective

Abstract Recent studies suggest that stratospheric wind biases in global and climate models in the Southern Hemisphere may result from insufficient orographic wave drag, particularly over the Southern Ocean in the latitude belt centered near 60°S. In this study, contributions to the stratospheric wave drag along 60°S from three neighboring orographic wave sources are evaluated using a multiple-layer linear wave model with large-scale wind and stratification profiles derived from the Interim ECMWF Re-Analysis (ERA-Interim) between the years 1991 and 2010. The orographic wave sources include the Patagonian peaks in the southern Andes, the Antarctic Peninsula, and the island of South Georgia. The climatological and dynamical aspects of the wave drag and its dependence on tropospheric winds are investigated. The results suggest that these orographic wave sources may have significant contributions to the stratospheric drag over the Southern Ocean through meridional spreading of the wave momentum flux aloft associated with three-dimensional wave propagation. Among the three locations considered, the wave drag from the Antarctic Peninsula is substantially larger than that from Patagonia and nearly two orders of magnitude larger than that from South Georgia island. The orographic wave drag is in general proportional to the westerly component of the surface winds and becomes virtually zero when the surface winds have an easterly component, associated with critical level absorption between the tropospheric easterlies and prevailing westerlies in the stratosphere. The derived wave drag exhibits substantial temporal variations, including synoptic-scale, month-to-month, and interannual variations.

A "Global Radiosonde and tracked-balloon Archive on Sixteen Pressure levels" (GRASP) going back to 1905 – Part 2: homogeneity adjustments for pilot balloon and radiosonde wind data

Abstract. This paper describes the comprehensive homogenization of the "Global Radiosonde and tracked balloon Archive on Sixteen Pressure levels" (GRASP) wind records. Many of those records suffer from artificial shifts that need to be detected and adjusted before they are suitable for climate studies. Time series of departures between observations and the National Atmospheric and Oceanic Administration 20th-century (NOAA-20CR) surface pressure only reanalysis have been calculated offline by first interpolating the observations to pressure levels and standard synoptic times, if needed, and then interpolating the gridded NOAA-20CR standard pressure level data horizontally to the observation locations. These difference time series are quite sensitive to breaks in the observation time series and can be used for both automatic detection and adjustment of the breaks. Both wind speed and direction show a comparable number of breaks, roughly one break in three stations. More than a hundred artificial shifts in wind direction could be detected at several US stations in the period 1938/1955. From the 1960s onward the wind direction breaks are less frequent. Wind speed data are not affected as much by measurement biases, but one has to be aware of a large fair-weather sampling bias in early years, when high wind speeds were much less likely to be observed than after 1960, when radar tracking was already common practice. This bias has to be taken into account when calculating trends or monthly means from wind speed data. Trends of both wind speed and direction look spatially more homogeneous after adjustment. With the exception of a widespread wind direction bias found in the early US network, no signs of pervasive measurement biases could be found. The adjustments can likely improve observation usage when applied during data assimilation. Alternatively they can serve as a basis for validating variational wind bias adjustment schemes. Certainly, they are expected to improve estimates of global wind trends. All the homogeneity adjustments are available in the PANGAEA archive with associated doi:10.1594/PANGAEA.823617.

The performance of Aeolus in heterogeneous atmospheric conditions using high-resolution radiosonde data

Abstract. The European Space Agency Aeolus mission aims to measure wind profiles from space. A major challenge is to retrieve high quality winds in heterogeneous atmospheric conditions, i.e. where both the atmospheric dynamics and optical properties vary strongly within the sampling volume. In preparation for launch we aim to quantify the expected error of retrieved winds from atmospheric heterogeneity, particularly in the vertical, and develop algorithms for wind error correction, as part of the level-2B processor (L2Bp). We demonstrate that high-resolution data from radiosondes provide valuable input to establish a database of collocated wind and atmospheric optics at 10 m vertical resolution to simulate atmospheric conditions along Aeolus' lines of sight. The database is used to simulate errors of Aeolus winds retrieved from the Mie and Rayleigh channel signals. The non-uniform distribution of molecules in the measurement bin introduces height assignment errors in Rayleigh channel winds up to 2.5% of the measurement bin size in the stratosphere which translates to 0.5 m s−1 bias for typical atmospheric conditions, if not corrected. The presence of cloud or aerosol layers in the measurement bin yields biases in Mie channel winds which cannot be easily corrected and mostly exceed the mission requirement of 0.4 m s−1. The collocated Rayleigh channel wind solution is generally preferred because of smaller biases, in particular for transparent cloud and aerosol layers with one-way transmission above 0.8. The results show that Aeolus L2Bp, under development, can be improved by the estimation of atmosphere optical properties to correct for height assignment errors and to identify wind solutions potentially detrimental when used in Numerical Weather Prediction.

What controls equatorial Atlantic winds in boreal spring?

The factors controlling equatorial Atlantic winds in boreal spring are examined using both observations and general circulation model (GCM) simulations from the coupled model intercomparison phase 5. The results show that the prevailing surface easterlies flow against the attendant pressure gradient and must therefore be maintained by other terms in the momentum budget. An important contribution comes from meridional advection of zonal momentum but the dominant contribution is the vertical transport of zonal momentum from the free troposphere to the surface. This implies that surface winds are strongly influenced by conditions in the free troposphere, chiefly pressure gradients and, to a lesser extent, meridional advection. Both factors are linked to the patterns of deep convection. Applying these findings to GCM errors indicates, that, consistent with the results of previous studies, the persistent westerly surface wind bias found in most GCMs is due mostly to precipitation errors, in particular excessive precipitation south of the equator over the ocean and deficient precipitation over equatorial South America. Free tropospheric influences also dominate the interannual variability of surface winds in boreal spring. GCM experiments with prescribed climatological sea-surface temperatures (SSTs) indicate that the free tropospheric influences are mostly associated with internal atmospheric variability. Since the surface wind anomalies in boreal spring are crucial to the development of warm SST events (Atlantic Ninos), the results imply that interannual variability in the region may rely far less on coupled air–sea feedbacks than is the case in the tropical Pacific.

Correcting Marine Surface Winds Simulated in Atmospheric Models Using Spatially and Temporally Varying Linear Regression

Abstract This study examines the application of three different variations of linear-regression corrections to the surface marine winds from the Australian Bureau of Meteorology’s recently implemented operational atmospheric model. A simple correction over the entire domain is found to inadequately account for geographical variation in the wind bias. This is addressed by considering corrections that vary in space. Further, these spatially varying corrections are extended to vary in time. In an operational environment, the error characteristics of the wind forcing can be expected to change over time with the evolution of the atmospheric model. This in turn requires any applied correction to be monitored and maintained. Motivated by a desire to avoid this manual maintenance, a self-learning correction method is proposed whereby spatially and temporally varying corrections are calculated in real time from a moving window of historical comparisons between observations and preceding forecasts. This technique is shown to effectively remove both global and regionally varying wind speed biases.

An Assessment of Atmospheric Water Budget Components over Tropical Oceans

Abstract Balancing global moisture budgets is a difficult task that is even more challenging at regional scales. Atmospheric water budget components are investigated within five tropical (15°S–15°N) ocean regions, including the Indian Ocean, three Pacific regions, and one Atlantic region, to determine how well data products balance these budgets. Initially, a selection of independent observations and a reanalysis product are evaluated to determine overall closure, between 1998 and 2007. Satellite-based observations from SeaFlux evaporation and Global Precipitation Climatology Project (GPCP) precipitation, together with Interim ECMWF Re-Analysis (ERA-Interim) data products, were chosen. Freshwater flux (evaporation minus precipitation) observations and reanalysis atmospheric moisture divergence regional averages are assessed for closure. Moisture budgets show the best closure over the Indian Ocean with a correlation of 89% and an overall imbalance of −3.0% of the anomalies. Of the five regions, the western Pacific Ocean region produces the worst atmospheric moisture budget closure of −21.1%, despite a high correlation of 93%. Average closure over the five regions is within 8.1%, and anomalies are correlated at 83%. ERA-Interim and Modern-Era Retrospective Analysis for Research and Applications (MERRA) evaporation rates are 29 and 19 mm month−1 greater than SeaFlux, respectively. To diagnose the differences, wind speed and humidity gradients of the three products are compared utilizing the bulk formula for evaporation. SeaFlux wind speeds are higher, but sea–air humidity gradients are lower. Higher humidity gradients in the reanalyses are due to much dryer near-surface air in ERA-Interim, and the same to a lesser degree in MERRA. These differences counteract each other somewhat, but overall humidity biases exceed wind biases. This is consistent with buoy observations.

Are atmospheric biases responsible for the tropical Atlantic SST biases in the CNRM-CM5 coupled model?

In this study, the CNRM-CM5 model is shown to simulate too warm SSTs in the tropical Atlantic as most state-of-the-art CMIP5 models. The warm bias develops within 1 or 2 months in decadal experiments initialised in January using an observationally derived state. To better quantify the role of the atmospheric biases in initiating this warm SST bias, several sensitivity experiments have been performed. In a first set of experiments, the surface solar net heat flux sent to the ocean model is academically corrected over the southeastern tropical Atlantic Ocean. This correction locally reduces the warm SST bias by more than 50 % with some remote impacts over equatorial regions. In contrast, the solar heat flux correction has locally little impact on the spring cooling. A second set of experiments quantifies the role of surface winds, using a nudging technique. When applied in a narrow equatorial region, the wind correction mainly improves the SST annual cycle amplitude along the Equator. It promotes not only the spring cooling along the Equator in preconditioning the mixed-layer depth but also in the southeastern Atlantic along the African coast. These local and remote effects are attributed to the more realistic representation of the oceanic equatorial circulation, driven by corrected winds. These results are consistent with those reported by Wahl et al. (Clim Dyn 36:891–906, 2011) in a very similar study with the Kiel Climate Model. The solar and wind biases have comparable effects in their study, although the importance of off-equatorial winds is less clear in our study. Diagnosing the wind energy flux provides a physical understanding of the equatorial region. When combining the corrections of both the equatorial wind and the southeastern solar heat flux, no obvious feedback between them is evidenced. The present study also emphasizes the need to consider two time-scales, the annual mean and the seasonal cycle, as well as two regions, the equatorial and the southeastern Atlantic regions, to comprehensively address the Atlantic SST bias. As pointed out in Richter (Clim Dyn, doi: 10.1007/s00382-012-1624-5 , 2013), the need to improve the atmospheric component of the CNRM-CM model is emphasized, even though strong positive coupling feedbacks are highlighted.

Sources of uncertainty in projections of twenty-first century westerly wind changes over the Amundsen Sea, West Antarctica, in CMIP5 climate models

The influence of changes in winds over the Amundsen Sea has been shown to be a potentially key mechanism in explaining rapid loss of ice from major glaciers in West Antarctica, which is having a significant impact on global sea level. Here, Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model data are used to assess twenty-first century projections in westerly winds over the Amundsen Sea (U AS ). The importance of model uncertainty and internal climate variability in RCP4.5 and RCP8.5 scenario projections are quantified and potential sources of model uncertainty are considered. For the decade 2090–2099 the CMIP5 models show an ensemble mean twenty-first century response in annual mean U AS of 0.3 and 0.7 m s−1 following the RCP4.5 and RCP8.5 scenarios respectively. However, as a consequence of large internal climate variability over the Amundsen Sea, it takes until around 2030 (2065) for the RCP8.5 response to exceed one (two) standard deviation(s) of decadal internal variability. In all scenarios and seasons the model uncertainty is large. However the present-day climatological zonal wind bias over the whole South Pacific, which is important for tropical teleconnections, is strongly related to inter-model differences in projected change in U AS (more skilful models show larger U AS increases). This relationship is significant in winter (r = −0.56) and spring (r = −0.65), when the influence of the tropics on the Amundsen Sea region is known to be important. Horizontal grid spacing and present day sea ice extent are not significant sources of inter-model spread.

A Study of Nocturnal Surface Wind Speed Overprediction by the WRF-ARW Model in Southeastern Texas

AbstractThe overprediction of surface wind speed during nighttime by the Advanced Research core of the Weather Research and Forecasting (WRF-ARW) model was investigated for a period of the Second Texas Air Quality Study (28 May–3 July 2006). In coastal regions of southeastern Texas, the model had a significant increase of wind speed biases on the surface in the evening throughout the period, especially between 4 and 12 June. The synoptic pattern was a high pressure system centered over the Louisiana–Mississippi area that was subjected to a weak easterly–southeasterly flow in the lower troposphere. The weather conditions favorable for sea-breeze development brought a southerly–southwesterly onshore flow to the near-surface levels. In comparison with measurements, the downward sensible heat flux was overpredicted at night, which resulted in a warm bias in surface temperature. For the vertical wind profile on days with an evening wind bias, sea-breeze-driven nocturnal low-level jets (southerly–southwesterly) were present at around 300 m while another wind maximum was observed at higher levels (around 1.5–2 km), which were associated with a high pressure system centered on southeastern states. The vertical gradient of wind speed in the lowest 150 m was smoother in the model than it was in the observations; this could be attributed to excessive downward mixing. Sensitivities using different land surface and PBL parameterizations showed that the model's overprediction of nocturnal wind was still present despite improvements in the predictions of surface temperature and sensible heat flux.

Diagnosing Northern Hemisphere Jet Portrayal in 17 CMIP3 Global Climate Models: Twentieth-Century Intermodel Variability

Abstract The present study focuses on diagnosing the intermodel variability of nonzonally averaged NH winter jet stream portrayal in 17 global climate models (GCMs) from phase three of the Coupled Model Intercomparison Project (CMIP3). Relative to the reanalysis, the ensemble-mean 300-hPa Atlantic jet is too zonally extended and located too far equatorward in GCMs. The Pacific jet varies significantly between modeling groups, with large biases in the vicinity of the jet exit region that cancel in the ensemble mean. After seeking relationships between twentieth-century model wind biases and 1) the internal modes of jet variability or 2) tropical sea surface temperatures (SSTs), it is found that biases in upper-level winds are strongly related to an ENSO-like pattern in winter-mean tropical Pacific Ocean SST biases. The spatial structure of the leading modes of variability of the upper-level jet in the twentieth century is found to be accurately modeled in all 17 GCMs. Also, it is shown that Pacific model biases in the longitude of EOFs 1 and 2 are strongly linked to the modeled longitude of the Pacific jet exit, indicating that the improved characterization of the mean state of the Pacific jet may positively impact the modeled variability. This work suggests that improvements in model portrayal of the tropical Pacific mean state may significantly advance the portrayal of the mean state of the Pacific and Atlantic jets, which will consequently improve the modeled jet stream variability in the Pacific. To complement these findings, a companion paper examines the twenty-first-century GCM projections of the nonzonally averaged NH jet streams.