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At least 325 records · Page 18

Monitoring Mars with the Hubble Space Telescope: 1990-1991 observations

Images of Mars obtained using the Planetary Camera on the Hubble Space Telescope during 1990 and 1991 are described and analyzed. Multispectral images of Mars record the martian season between L(sub s) = 348 deg and 60 deg corresponding to late winter and spring in the northern hemisphere. The wavelengths of these observations varied between 230 nm in the ultraviolet and 890 nm in the near infrared. We use these images to discuss atmospheric and polar phenomena, to constrain the aerosols and ozone in the martian atmosphere, and to compare surface albedo features within this data set as well as with previous observations. Two methods are used to constrain the opacity of the martian atmosphere: comparisons of ultraviolet images with atmospheric scattering models and examination of contrast changes of surface features observed at visible wavelengths. Our observations are consistent with a Mars which was quite different from the planet when it was viewed by Viking; we estimate an upper limit of 0.1 for equatorial dust opacity near vernal equinox, compared to values of 0.4 to 0.5 measured in Chryse by Viking Lander 1. Later, at L(sub s) = 60 deg, and upper limit of 0.2 was found for dust in the southern hemisphere. Except for suggestions of local dust activity near the north polar cap in late spring, there was no visual evidence of dust storms on the planet. The Hartley band of ozone is within the F230W filter bandpass, and the 230W/336W ratio is therefore sensitive to ozone. High latitude ozone is observed at a concentration similar to that observed by Mariner 9; a seasonal dependence in ozone concentration was observed with concentration decreasing at northern arctic latitudes and increasing at southern midlatitudes as L(sub s) increases from 350 deg to 60 deg. Despite the difference in dust loading, the behavior of condensate clouds and the recession of the north polar cap are consistent with those observed during Viking years. Late winter images of the north polar region reveal an active north polar hood with a maximum (UV) opacity of about 0.25 near 50 deg latitude; the hood seems to have an annular form, with the central, polar regions having smaller opacity. Clouds observed in the northern hemisphere to the south of the hood boundary are suggestive of fronts similar to those observed during the Mariner 9 mission. A diurnal variation in the hood clouds which is (anti) correlated with the amount of water vapor in the atmosphere is noted. Images were deconvolved using the Richardson-Lucy iterative algorithm to remove the defocussing effects of the spherical aberration of the HST primary. Even when Mars subtended less than 5 arcsec, in May 1991, the images were scientifically useful and comparable to photographic images obtained at opposition. Although the data are subject to the solar pointing constraint for HST, the relatively slow movement of the allowed observation window, which is more than one half martian year, with respect to the martian seasons will permit us to address the question of major variations in the martian atmosphere.

James, Philip B.↗

Pioneer 10 ultraviolet photometer observations of Jovian UV emission in 1973

The Pioneer 10 ultraviolet measurements obtained during the Jupiter encounter in 1973 have been further examined by using improved data handling and analysis techniques. The Pioneer 10 observations of Jupiter and its satellites during the encounter have been carefully reviewed in order to improve our understanding of the morphology of the Io plasma torus and Jupiter's upper atmosphere and to investigate the possible existence of other emission source such as Europa. In addition, the morphology of Io's bimodal torus observed during the Pioneer 10 encounter has been compared with the Voyager observations obtained approximately 6 years after the Pioneer 10 flyby and significant differences in the torus characteristics are found. The Io torus in 1973 was more similar to the 1992 Ulysses observations of a longitudinally asymmetric ring than to the complete ring observed by Voyager. Pioneer 10 observed a significantly dimmer Io torus and Jupiter upper atmosphere in the EUV compared to the Voyager observations. Apart from the torus and Jupiter, Pioneer 10 observed additional emissions which have been attributed to Io itself. Three distinct possibilities have been discussed to explain these additional emissions. The most likely is that Pioneer 10 observed volcanism on Io. There is also evidence of Pioneer 10 observing emissions from Europa. The present analysis clearly shows that the Jovian system in 1973 was significantly different from that observed in 1979.

Wu, F. M.↗

Microwave Observations and Modeling of O2 (1-delta(sub g)) and O3 Diurnal Variation in the Mesosphere

The first microwave measurements of an electronically excited molecular species in the Earth's atmosphere are presented. Local thermodynamic equilibrium (LTE) rotational line emission from mesospheric O2(1-del(sub g)) was observed at a frequency of 255.01794 GHz (lambda is approx. 1.2 mm), employing the National Radio Astronomy Observatory (NRAO) millimeter facility at Kitt Peak, Arizona (32 N, 111 W). The pressure broadened line shapes of the O2(1-del(sub g)) spectra, which were obtained in January and April 1992 and in January and November 1993, are inverted to retrieve O2(1-del(sub g)) mixing profiles over the 50-70 km altitude region. The observed daytime abundances exceed ozone abundances in the lower mesosphere, which are separately retrieved with coincident O3 spectral line (249.7886 GHz) observations. The January and November 1993 observations are binned into 20-60 min time intervals to study O2(1-del(sub g)) diurnal behavior. Derived abundances of O2(1-del(sub g)) between 50 and 70 km for the four observation dates are 9%, 31%, 3%, and 26%, respectively, each +/- 10% higher than predicted, based on the simple photochemistry of lower mesospheric O2(1-del(sub g)). Modeled variation of [O2(1-del(sub g))] with time of day agrees with observed variation in that the observed difference between model and data abundances is constant throughout the daylight hours of each observation date. Model underprediction Of [02(lAg)] is consistent with similar model underprediction of mesospheric [O3]. A perturbation to the photochemical model that forces decreased ozone chemical loss brings brings both model [O3] and [O2(1-del(sub g))] into agreement with the observations. O2(1-del(sub g)) abundances derived from these 1.2 mm observations agree with [O2(1-del(sub g))] values derived from comparable SME observations of the 1.27 micrometers emission, with assumption of a 3880 sec O2(1-del(sub g)) radiative lifetime. The 6800 sec O2(1-del(sub g)) radiative lifetime proposed by Mlynczak and Nesbitt is ruled out by the similar comparison.

Sandor, Brad J.↗

Nonlinear Observers for Gyro Calibration

High precision estimation and control algorithms, to achieve unprecedented levels of pointing accuracy, will be required to support future formation flying missions such as interferometry missions. Achieving high pointing accuracy requires precise knowledge of the spacecraft rotation rate. Typically, the rotation rate is measured by a gyro. The measured rates can be corrupted by errors in alignment and scale factor, gyro biases, and noise. In this work, we present nonlinear observers for gyro calibration. Nonlinear observers are superior to extended or pseudo-linear Kalman filter type approaches for large errors and global stability. Three nonlinear gyro calibration observers are developed. The first observer estimates a constant gyro bias. The second observer estimates scale factor errors. The third observer estimates the gyro alignment for three orthogonal gyros. The convergence properties of all three observers are discussed. Additionally, all three observers are coupled with a nonlinear control algorithm. The stability of each of the resulting closed loop systems is analyzed. The observers are then combined, and the gyro calibration parameters are estimated simultaneously. The stability of the combined observers is addressed, as well as the stability of the resulting closed loop systems. Simulated test results are presented for each scenario. Finally, the nonlinear observers are compared to a pseudo-linear Kalman filter.

Thienel, Julie↗

Multi-Year Characterization of PSCs Using Solar Occultation Satellite Observations

POAM solar occultation observations from1994 to present are studied for the purpose of determining Type I PSC formation characteristics and winter-long evolution. This information is critical to an improved understanding and predictive capability of stratospheric ozone depletion. Solar occultation satellite observations of these clouds yields more continuous and wide-spread information than can be obtained from aircraft, balloon, or ground-based observations. This multi-winter PSC study is augmented by the use of our Type Ia/Ib discrimination scheme. Recent studies of PSC formation made with POAM observations and simulations during the 1999-2000 Arctic winter have shown characteristics that shed light on the formation mechanisms responsible for Type Ia solid phase PSCs. This study examines PSC observations from many years on a common basis to see if the characteristics observed & cuing the 1999-2000 Arctic winter ai-e observed in other years and if other characteristics can be identified. The results show that Type Ia PSCs form at the beginning of the winter, within several days of the fxst drop in temperature below TNAT, and peak early in the winter. Type Ia PSCs typically outnumber Ib PSCs over the winter, especially at the beginning of the winter. Type Ia and Ib PSC observations continue throughout the winter. Micro-physical models of PSC formation must match these observed characteristics. Some models predict that temperatures must be more 5 K below T-NAT for five days before significant freezing can occur. This is not seen in the POAM observations. Differences in PSC characte ristics between the first two Arctic winters (1 994- 1995 and 1995- 1 996) and later winters also suggest the influence of volcanic perturb ations on PSC formation. Type Ia and Ib PSC characteristics observed by POAM III and SAGE III for the 2002-2003 Arctic winter are compared.

Strawa, A. W.↗

Students as Ground Observers for Satellite Cloud Retrieval Validation

The Students' Cloud Observations On-Line (S'COOL) Project was initiated in 1997 to obtain student observations of clouds coinciding with the overpass of the Clouds and the Earth's Radiant Energy System (CERES) instruments on NASA's Earth Observing System satellites. Over the past seven years we have accumulated more than 9,000 cases worldwide where student observations are available within 15 minutes of a CERES observation. This paper reports on comparisons between the student and satellite data as one facet of the validation of the CERES cloud retrievals. Available comparisons include cloud cover, cloud height, cloud layering, and cloud visual opacity. The large volume of comparisons allows some assessment of the impact of surface cover, such as snow and ice, reported by the students. The S'COOL observation database, accessible via the Internet at http://scool.larc.nasa.gov, contains over 32,000 student observations and is growing by over 700 observations each month. Some of these observations may be useful for assessment of other satellite cloud products. In particular, some observing sites have been making hourly observations of clouds during the school day to learn about the diurnal cycle of cloudiness.

Chambers, Lin H.↗

New Observations of the Heliospheric Magnetic Field from the Voyager Spacecraft

We review recent observations of variations of the heliospheric magnetic field B(t) made by Voyager 1 and 2 (V1 and V2), and we discuss the boundary conditions needed for models to explain the observations. Usually, observations from a spacecraft close to the Sun, such as ACE, WIND or Ulysses are used as input to a time-dependent model. Generally, the predicted profile B(t) can be compared directly with the observed profile only when either V1 or V2 is approximately radially aligned with a near-Sun spacecraft; this happens rarely and only for a brief time interval. The Bastille Day events illustrate this situation. In the absence of radial alignment of the spacecraft it is possible to predict the development of a global structure (a GMIR) with data from ACE or WIND, if they obtain a representative sample the flows that merge to form a GMIR. When latitudinal gradients are small and when there is statistical homogeneity in the azimuthal direction, it is possible to predict the statistical properties of the large-scale fluctuations of B(t) observed by V1 or V2 during a year or so. We illustrate this situation with observations from the recent solar maximum and the declining phase of the solar cycle. Predictions of detailed observations made by V1 and V2 under general conditions (e.g., when there is a large latitudinal gradient) require boundary conditions as a function of time on a surface, such as a Sun-centered sphere with a radius of 1 AU. These conditions can only be provided by global solar observations. We suggest the feasibility of such an approach, using V2 observations for 2005 and 2006. The prediction of observations in the heliosheath requires the solution of the 3-D boundary problem for the supersonic solar wind and propagation of solar wind through the termination shock into the heliosphere. The properties of B(t) observed in the heliosheath have not yet been predicted.

Burlaga, Leonard F.↗

HOx Observation and Model Comparison During INTEX-A 2004

OH and HO2 were measured with the Airborne Tropospheric Hydrogen Oxides Sensor (ATHOS) as part of a large measurement suite from the NASA DC-8 aircraft during the Intercontinental Chemical Transport Experiment - A (INTEX-A). This mission, which was conducted mainly over North America and the western Atlantic Ocean in summer 2004, was an excellent test of atmospheric oxidation chemistry. Throughout the troposphere, observed OH was generally 0.60 of the modeled OH; below 8 km, observed HO2 was generally 0.78 of modeled HO2. If the over-prediction of tropospheric OH is not due to an instrument calibration error, then it implied less global tropospheric oxidation capacity and longer lifetimes for gases like methane and methyl chloroform than currently thought. This discrepancy falls well outside uncertainties in both the OH measurement and rate coefficients for known reactions and points to a large unknown OH loss. If the modeled OH is forced to agree with observed values by introducing of an undefined OH loss that removed HOx (HOx=OH+HO2), the observed and modeled HO2 and HO2/OH ratios are largely reconciled within the measurement uncertainty. HO2 behavior above 8 km was markedly different. The observed-to-modeled ratio correlating with NO. The observed-to-modeled HO2 ratio increased from approximately 1 at 8 km to more than approximately 2.5 at 11 km with the observed-to-modeled ratio correlating with NO. The observed-to-modeled HO2 and NO were both considerably greater than observations from previous campaigns. In addition, the observed-to-modeled HO2/OH, which is sensitive to cycling reactions between OH and HO2, increased from approximately 1.2 at 8 km to almost 4 above 11 km. In contrast to the lower atmosphere, these discrepancies above 8 km suggest a large unknown HOx source and additional reactants that cycle HOx from OH to HO2. In the continental planetary boundary layer, the OH observed-to-modeled ratio increased from 0.6 when isoprene was less than 0.1 ppbv to over 3 when isoprene was greater than 2 ppbv, suggesting that forests throughout the United States are emitting unknown HOx sources. Progress in resolving these discrepancies requires further examinations of possible unknown OH sinks and HOx sources and a focused research activity devoted to ascertaining the accuracy of the OH and HO2 measurements.

Ren, Xinrong↗

Chemical Source Inversion using Assimilated Constituent Observations in an Idealized Two-dimensional System

We present a source inversion technique for chemical constituents that uses assimilated constituent observations rather than directly using the observations. The method is tested with a simple model problem, which is a two-dimensional Fourier-Galerkin transport model combined with a Kalman filter for data assimilation. Inversion is carried out using a Green's function method and observations are simulated from a true state with added Gaussian noise. The forecast state uses the same spectral spectral model, but differs by an unbiased Gaussian model error, and emissions models with constant errors. The numerical experiments employ both simulated in situ and satellite observation networks. Source inversion was carried out by either direct use of synthetically generated observations with added noise, or by first assimilating the observations and using the analyses to extract observations. We have conducted 20 identical twin experiments for each set of source and observation configurations, and find that in the limiting cases of a very few localized observations, or an extremely large observation network there is little advantage to carrying out assimilation first. However, in intermediate observation densities, there decreases in source inversion error standard deviation using the Kalman filter algorithm followed by Green's function inversion by 50% to 95%.

Tangborn, Andrew↗

Comparing Two Approaches for Assessing Observation Impact

Langland and Baker introduced an approach to assess the impact of observations on the forecasts. In that approach, a state-space aspect of the forecast is defined and a procedure is derived ultimately relating changes in the aspect with changes in the observing system. Some features of the state-space approach are to be noted: the typical choice of forecast aspect is rather subjective and leads to incomplete assessment of the observing system, it requires availability of a verification state that is in practice correlated with the forecast, and it involves the adjoint operator of the entire data assimilation system and is thus constrained by the validity of this operator. This article revisits the topic of observation impacts from the perspective of estimation theory. An observation-space metric is used to allow inferring observation impact on the forecasts without the limitations just mentioned. Using differences of observation-minus-forecast residuals obtained from consecutive forecasts leads to the following advantages: (i) it suggests a rather natural choice of forecast aspect that directly links to the data assimilation procedure, (ii) it avoids introducing undesirable correlations in the forecast aspect since verification is done against the observations, and (iii) it does not involve linearization and use of adjoints. The observation-space approach has the additional advantage of being nearly cost free and very simple to implement. In its simplest form it reduces to evaluating the statistics of observationminus- background and observation-minus-analysis residuals with traditional methods. Illustrations comparing the approaches are given using the NASA Goddard Earth Observing System.

Variational Analysis↗

Building a standardized Observing System Simulation Experiment (OSSE) framework for Mars

We advocate that the Decadal Survey recommends the NASA Science Mission Directorate to develop a rigorous Observing System Simulation Experiment (OSSE) framework for Mars, to optimize future atmospheric observations. Atmospheric conditions on Mars are a potential hazard source for landing missions. Errors in the estimates of atmospheric density profiles, inadequate knowledge of wind vertical structure and dust concentration as a function of height are likely causes of uncertainty at the landing site on the order of kilometers. An operational real-time weather forecasting capability for Mars would reduce such uncertainties, carrying enormous benefits to future robotic missions, and would be an invaluable prerequisite for human missions.A real-time forecasting capability relies upon three fundamental components: a critical mass of observing systems, a data assimilation system (DAS), and a global forecast model. The DAS allows the model to ingest the data effectively, optimizing the observational information content,and transforming them into a gridded representation of the atmosphere at a given time, called an ‘analysis’. The analysis is the best estimate of the atmospheric state for that time, and also represents a set of ‘initial conditions’ from which a global model can be initialized, to predict a future state of the atmosphere. The connection between analysis and forecast represents the foundation of modern weather forecasting. However, from the point of view of a forecast system,not all observations are equally impactful, partially because of the problem of “observational error correlation”, one important research topic in data assimilation development. For the Earth, partly due to the spontaneous and deregulated development of observations and forecast capabilities worldwide for more than half a century,the use of observations in contemporary operational forecast systems is suboptimal, with many potentially useful data being underutilized. On the contrary, Mars atmospheric scientists are in the unique situation of designing the next-generation observing systems by learning from the experience gathered on the Earth, so as to assure that the future instruments are specifically optimized to give the maximum benefit to a future weather forecast capability.An immensely powerful tool that has been firmly established by atmospheric scientists on the Earth is represented by a properly designed OSSE framework. A realistic OSSE framework cannot only quantify the benefit of future data types, be them surface based or space borne, but can also help design and optimize an entire observational network. Furthermore, OSSEs can provide deep insights into an atmosphere’s behavior, by addressing conceptual problems of its intrinsic predictability and delineating the regions or features of the atmosphere which are more sensitive to additional data and would benefit from a denser sampling. The difficulties posed by OSSEs are fundamentally different for Earth and Mars. For Earth, the enormous data volume imposes a tremendous constraint on any innovation in the observing systems: it is very hard for a single sensor to impact the skill. For Mars, the problem is the opposite: almost any additional instrument will exert some impact. However, OSSEs can help to evaluate the cost/benefit for every sensor and suggest optimal data configuration and density.The purpose of this white paper is to provide an introduction to a rigorously designed OSSE framework, explain the underlying problems and challenges, and engage the Mars community to collaborate with Earth Atmospheric scientists in order to develop a joint-OSSE framework for Mars with the largest consensual basis possible. An OSSE infrastructure would increase the understanding of the Martian atmosphere, would help NASA to optimize instrument specifications and orbit choice, providing the maximium benefit for a given expenditure of resources, and could even help establishing a roadmap for a future real-time weather forecasting capability.

Oreste Reale↗

Retrospective Observations of the Solar System Planets with Interstellar Probe

Retrospective Observations of the Solar System Planets with Interstellar Probe The Interstellar Probe (ISP) mission concept could simultaneously explore a number of long-standing solar system and exoplanetary science objectives. ISP’s long mission lifetime, in combination with the large separations from the solar system objects it could observe (Fig. 1), affords a truly unique dataset. This data could be leveraged to validate models of solar system and extrasolar planets and would be directly analogous to observations we can expect to make for exoplanets. Taken together, these opportunities suggest that ISP’s mission is a critical and necessary component for future planetary science endeavors. This abstract aims to address some of the clear synergies between ISP’s mission profile and the gaps in solar system science that are necessarily gaps in our ability to wholly bound our expectations for exoplanet observations (partly discussed in several white papers, including Zemcov et al., 2019; Harman et al., 2020). Notably, no single platform has yet returned near-complete phase curves for the majority of solar system planets. This is partly due to observational constraints (e.g., ground-based observatories can observe a maximum phase angle of Jupiter, Saturn, Uranus, and Neptune of 12º, 6º, 3º, and 2º, respectively; Mallama and Hilton, 2018), but also because of the sparse nature of observations captured by spacecraft over the last 40 years (e.g., Pollack et al., 1986). Additionally, these observations come from disparate instruments that have their own biases and limitations, whereas observations by ISP’s instrumentation would provide almost uniform measurements of nearly every solar system object, removing much of the uncertainty when it comes to data intercomparisons. The biggest hurdles for making these measurements from ISP are likely to be the tight mass and energy limitations, as well as the technical challenge of looking as close as possible to the Sun without peering directly at it. This is potentially complicated by the nature of the larger astrophysical mission requirements, including whether the spacecraft is spinning, but integrating observations on board before returning them to Earth serves to both partly mitigate both the possibility of a spinning spacecraft and the downlink volumes for lookback data (although it may make data disaggregation more technically challenging). Ultimately, ISP could return truly innovative observational data of our solar system, in furtherance of a number of planetary and solar system science goals.

Sonny Harman↗

Synergistic Retrievals of Ice in High Clouds From Elastic Backscatter Lidar, Ku-band Radar and Submillimeter Wave Radiometer Observations

In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and sub-millimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of IceWater Content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments e.g. frequencies, sensitivities, etc. are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, out of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-Means clustering algorithm. In the second step, the IWC profile is estimated using an Ensemble Kalman Smoother (EKS) algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.

Mircea Grecu↗

Enabling the Assimilation of CrIS Shortwave Infrared Observations in Global NWP at NOAA. Part II: OSEs and Results

The assimilation of data from hyperspectral infrared sounders in global data assimilation systems has historically been focused on observations in the longwave infrared (LWIR) region of the spectrum (650-1100 cm−1), despite the often concurrent availability of measurements from the shortwave infrared (SWIR) region of the spectrum (2150-2550 cm−1), because issues (like solar effects) have generally prevented the assimilation of SWIR observations. Recent advances in radiative transfer models have worked to address some of the previous challenges in simulating SWIR observations, and the assimilation of SWIR data (e.g. from potential future small-satellites) is now a feasible prospect. Still, a better understanding of how these observations perform in a data assimilation system and impact resulting analyses and NWP forecasts is necessary. In this study, the value of SWIR observations in global NWP is assessed by assimilating SWIR observations from the Cross-track Infrared Sounder (CrIS) in NOAA’s Global Data Assimilation System (GDAS). The methodologies used to enable the assimilation of these observations, including the implementation of a scene-dependent observation error and the enhancement of quality control procedures, are discussed, as are the results of Observing System Experiments (OSEs) conducted to evaluate the impact of assimilating SWIR observations on forecast skill. The overall results show that SWIR assimilation produces similar forecast impacts to LWIR assimilation. The ability to demonstrate that the assimilation or SWIR observations in NWP is a realistic prospect may help to shape future constellations of small-satellites to serve as a beneficial complement to the current constellation if hyperspectral IR sounders.

Erin Jones↗

Mesoscale evaluation of AMPS using AWARE radar observations of a wind and precipitation event over the Ross Island region of Antarctica

Surface, upper-air, and radar observations are used to assess the performance of the Antarctic Mesoscale Prediction System (AMPS) in simulating the mesoscale aspects of a wind and precipitation event over the Ross Island region of Antarctica that spanned January 16–20, 2016. The observations, collected during the Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE), provide a unique dataset for evaluating AMPS, especially the radar observations that facilitate a three-dimensional depiction of winds and precipitation. Comparisons of AMPS forecast data with surface meteorology, balloon-sounding, and profiling radar observations at and above sites near McMurdo Station reveal a mixture of similarities and differences. A generally southerly flow is evident at low levels in both the AMPS simulations and observed Doppler radial velocities. AMPS winds are comparable to those observed at the surface and aloft in terms of magnitude, direction, and timing but the strongest simulated southerly flow is displaced eastward relative to the observations. AMPS-simulated reflectivity over the broader Ross Island region is more limited in areal extent and smaller in magnitude than observed by a scanning Doppler radar. Three episodes of surface precipitation are observed near McMurdo Station over the five-day event with peak rates of ~3 mm h -1 and a total accumulation of ~22 mm. However, AMPS produces no surface precipitation at that location over the five-day event due to a low-level dry bias in the forecasts. Herein, the results show the first observationally based three-dimensional understanding of meteorology in the Ross Island region.

AMPS↗

Nudging allows direct evaluation of coupled climate models with in situ observations: a case study from the MOSAiC expedition

Comparing the output of general circulation models to observations is essential for assessing and improving the quality of models. While numerical weather prediction models are routinely assessed against a large array of observations, comparing climate models and observations usually requires long time series to build robust statistics. Here, we show that by nudging the large-scale atmospheric circulation in coupled climate models, model output can be compared to local observations for individual days. We illustrate this for three climate models during a period in April 2020 when a warm air intrusion reached the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in the central Arctic. Radiosondes, cloud remote sensing and surface flux observations from the MOSAiC expedition serve as reference observations. The climate models AWI-CM1/ECHAM and AWI-CM3/IFS miss the diurnal cycle of surface temperature in spring, likely because both models assume the snowpack on ice to have a uniform temperature. CAM6, a model that uses three layers to represent snow temperature, represents the diurnal cycle more realistically. During a cold and dry period with pervasive thin mixed-phase clouds, AWI-CM1/ECHAM only produces partial cloud cover and overestimates downwelling shortwave radiation at the surface. AWI-CM3/IFS produces a closed cloud cover but misses cloud liquid water. Our results show that nudging the large-scale circulation to the observed state allows a meaningful comparison of climate model output even to short-term observational campaigns. We suggest that nudging can simplify and accelerate the pathway from observations to climate model improvements and substantially extends the range of observations suitable for model evaluation.

54 ENVIRONMENTAL SCIENCES↗

Observations of wind farm wake recovery at an operating wind farm

Abstract. The interplay of momentum surrounding wind farms significantly influences wake recovery, affecting the speed at which wakes return to their freestream velocities. Under stable atmospheric conditions, wind farm wakes can extend over considerable distances, leading to sustained vertical momentum flux downstream, with variations observed throughout the diurnal cycle. Particularly in regions such as the US Great Plains, stable conditions can induce low-level jets (LLJs), impacting wind farm performance and power output. This study examines the implications of wake recovery using long-term observations of vertical momentum flux profiles across diverse atmospheric conditions. In these observations, several key findings were observed, such as (a) LLJ heights being altered downstream of a wind farm, especially when the LLJs are below 250 m above ground level; (b) a notable impact of LLJ height on wake recovery being observed using momentum flux profiles at upwind and downwind locations, wherein LLJs between 250 and 500 m above ground level resulted in larger momentum transfer within the wake (i.e., smaller velocity deficit) compared to LLJs below 250 m above ground level; (c) the largest momentum flux variability being observed during stable atmospheric conditions, with non-negligible variability observed during neutral and unstable atmospheric conditions; (d) detection of wake effects almost always being observed throughout the atmospheric boundary layer height; and finally (e) enhancement of wake recovery being observed in the presence of propagating gravity waves. These insights deepen our understanding of the intricate dynamics governing wake recovery in wind farms, advancing efforts to model and predict their behavior across varying atmospheric contexts. In addition, the performance of large-eddy-simulation-based semi-empirical internal boundary layer height model estimates incorporating real-world atmospheric and turbine inputs was evaluated using observations during LLJ conditions.

17 WIND ENERGY↗

Observing Arctic Sea Ice

Our understanding of Arctic sea ice and its wide-ranging influence is deeply rooted in observation. Advancing technologies have profoundly improved our ability to observe Arctic sea ice, document its processes and properties, and describe atmosphere-ice-ocean interactions with unprecedented detail. Yet, our progress toward better understanding the Arctic sea ice system is mired by the stark disparities between observations that tend to be siloed by method, scientific discipline, and application. This article presents a review and philosophical design for observing sea ice and accelerating our understanding of the Arctic sea ice system. We give a brief history of Arctic sea ice observations and showcase the 2018 melt season within the context of five observational themes: spatial heterogeneity, temporal variability, cross-disciplinary science, scalability, and retrieval uncertainty. We synthesize buoy data, optical imagery, satellite retrievals, and airborne measurements to demonstrate how disparate data sets can be woven together to transcend observational-scale issues. The results show that there are limitations to interpreting any single data set alone. However, many of these limitations can be surmounted by combining observations that cross spatial and temporal scales. We conclude the article with pathways toward coordinating across observational platforms in order to: (1) optimize the scientific, operational, and community return on observational investments, and (2) facilitate a richer understanding of Arctic sea ice and its role in the climate system.

54 ENVIRONMENTAL SCIENCES↗