The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

State of the climate in 2013

In 2013, the vast majority of the monitored climate variables reported here maintained trends established in recent decades. ENSO was in a neutral state during the entire year, remaining mostly on the cool side of neutral with modest impacts on regional weather patterns around the world. This follows several years dominated by the effects of either La Niña or El Niño events. According to several independent analyses, 2013 was again among the 10 warmest years on record at the global scale, both at the Earths surface and through the troposphere. Some regions in the Southern Hemisphere had record or near-record high temperatures for the year. Australia observed its hottest year on record, while Argentina and New Zealand reported their second and third hottest years, respectively. In Antarctica, Amundsen-Scott South Pole Station reported its highest annual temperature since records began in 1957. At the opposite pole, the Arctic observed its seventh warmest year since records began in the early 20th century. At 20-m depth, record high temperatures were measured at some permafrost stations on the North Slope of Alaska and in the Brooks Range. In the Northern Hemisphere extratropics, anomalous meridional atmospheric circulation occurred throughout much of the year, leading to marked regional extremes of both temperature and precipitation. Cold temperature anomalies during winter across Eurasia were followed by warm spring temperature anomalies, which were linked to a new record low Eurasian snow cover extent in May. Minimum sea ice extent in the Arctic was the sixth lowest since satellite observations began in 1979. Including 2013, all seven lowest extents on record have occurred in the past seven years. Antarctica, on the other hand, had above-average sea ice extent throughout 2013, with 116 days of new daily high extent records, including a new daily maximum sea ice area of 19.57 million km2 reached on 1 October. ENSO-neutral conditions in the eastern central Pacific Ocean and a negative Pacific decadal oscillation pattern in the North Pacific had the largest impacts on the global sea surface temperature in 2013. The North Pacific reached a historic high temperature in 2013 and on balance the globally-averaged sea surface temperature was among the 10 highest on record. Overall, the salt content in nearsurface ocean waters increased while in intermediate waters it decreased. Global mean sea level continued to rise during 2013, on pace with a trend of 3.2 mm yr-1 over the past two decades. A portion of this trend (0.5 mm yr-1) has been attributed to natural variability associated with the Pacific decadal oscillation as well as to ongoing contributions from the melting of glaciers and ice sheets and ocean warming. Global tropical cyclone frequency during 2013 was slightly above average with a total of 94 storms, although the North Atlantic Basin had its quietest hurricane season since 1994. In the Western North Pacific Basin, Super Typhoon Haiyan, the deadliest tropical cyclone of 2013, had 1-minute sustained winds estimated to be 170 kt (87.5 m s-1) on 7 November, the highest wind speed ever assigned to a tropical cyclone. High storm surge was also associated with Haiyan as it made landfall over the central Philippines, an area where sea level is currently at historic highs, increasing by 200 mm since 1970. In the atmosphere, carbon dioxide, methane, and nitrous oxide all continued to increase in 2013. As in previous years, each of these major greenhouse gases once again reached historic high concentrations. In the Arctic, carbon dioxide and methane increased at the same rate as the global increase. These increases are likely due to export from lower latitudes rather than a consequence of increases in Arctic sources, such as thawing permafrost. At Mauna Loa, Hawaii, for the first time since measurements began in 1958, the daily average mixing ratio of carbon dioxide exceeded 400 ppm on 9 May. The state of these variables, along with dozens of others, and the 2013 climate conditions of regions around the world are discussed in further detail in this 24th edition of the State of the Climate series. © 2014, American Meteorological Society. All rights reserved

State of the climate in 2018

In 2018, the dominant greenhouse gases released into Earth’s atmosphere—carbon dioxide, methane, and nitrous oxide—continued their increase. The annual global average carbon dioxide concentration at Earth’s surface was 407.4 ± 0.1 ppm, the highest in the modern instrumental record and in ice core records dating back 800 000 years. Combined, greenhouse gases and several halogenated gases contribute just over 3 W m−2 to radiative forcing and represent a nearly 43% increase since 1990. Carbon dioxide is responsible for about 65% of this radiative forcing. With a weak La Niña in early 2018 transitioning to a weak El Niño by the year’s end, the global surface (land and ocean) temperature was the fourth highest on record, with only 2015 through 2017 being warmer. Several European countries reported record high annual temperatures. There were also more high, and fewer low, temperature extremes than in nearly all of the 68-year extremes record. Madagascar recorded a record daily temperature of 40.5°C in Morondava in March, while South Korea set its record high of 41.0°C in August in Hongcheon. Nawabshah, Pakistan, recorded its highest temperature of 50.2°C, which may be a new daily world record for April. Globally, the annual lower troposphere temperature was third to seventh highest, depending on the dataset analyzed. The lower stratospheric temperature was approximately fifth lowest. The 2018 Arctic land surface temperature was 1.2°C above the 1981–2010 average, tying for third highest in the 118-year record, following 2016 and 2017. June’s Arctic snow cover extent was almost half of what it was 35 years ago. Across Greenland, however, regional summer temperatures were generally below or near average. Additionally, a satellite survey of 47 glaciers in Greenland indicated a net increase in area for the first time since records began in 1999. Increasing permafrost temperatures were reported at most observation sites in the Arctic, with the overall increase of 0.1°–0.2°C between 2017 and 2018 being comparable to the highest rate of warming ever observed in the region. On 17 March, Arctic sea ice extent marked the second smallest annual maximum in the 38-year record, larger than only 2017. The minimum extent in 2018 was reached on 19 September and again on 23 September, tying 2008 and 2010 for the sixth lowest extent on record. The 23 September date tied 1997 as the latest sea ice minimum date on record. First-year ice now dominates the ice cover, comprising 77% of the March 2018 ice pack compared to 55% during the 1980s. Because thinner, younger ice is more vulnerable to melting out in summer, this shift in sea ice age has contributed to the decreasing trend in minimum ice extent. Regionally, Bering Sea ice extent was at record lows for almost the entire 2017/18 ice season. For the Antarctic continent as a whole, 2018 was warmer than average. On the highest points of the Antarctic Plateau, the automatic weather station Relay (74°S) broke or tied six monthly temperature records throughout the year, with August breaking its record by nearly 8°C. However, cool conditions in the western Bellingshausen Sea and Amundsen Sea sector contributed to a low melt season overall for 2017/18. High SSTs contributed to low summer sea ice extent in the Ross and Weddell Seas in 2018, underpinning the second lowest Antarctic summer minimum sea ice extent on record. Despite conducive conditions for its formation, the ozone hole at its maximum extent in September was near the 2000–18 mean, likely due to an ongoing slow decline in stratospheric chlorine monoxide concentration. Across the oceans, globally averaged SST decreased slightly since the record El Niño year of 2016 but was still far above the climatological mean. On average, SST is increasing at a rate of 0.10° ± 0.01°C decade−1 since 1950. The warming appeared largest in the tropical Indian Ocean and smallest in the North Pacific. The deeper ocean continues to warm year after year. For the seventh consecutive year, global annual mean sea level became the highest in the 26-year record, rising to 81 mm above the 1993 average. As anticipated in a warming climate, the hydrological cycle over the ocean is accelerating: dry regions are becoming drier and wet regions rainier. Closer to the equator, 95 named tropical storms were observed during 2018, well above the 1981–2010 average of 82. Eleven tropical cyclones reached Saffir–Simpson scale Category 5 intensity. North Atlantic Major Hurricane Michael’s landfall intensity of 140 kt was the fourth strongest for any continental U.S. hurricane landfall in the 168-year record. Michael caused more than 30 fatalities and $25 billion (U.S. dollars) in damages. In the western North Pacific, Super Typhoon Mangkhut led to 160 fatalities and$6 billion (U.S. dollars) in damages across the Philippines, Hong Kong, Macau, mainland China, Guam, and the Northern Mariana Islands. Tropical Storm Son-Tinh was responsible for 170 fatalities in Vietnam and Laos. Nearly all the islands of Micronesia experienced at least moderate impacts from various tropical cyclones. Across land, many areas around the globe received copious precipitation, notable at different time scales. Rodrigues and Réunion Island near southern Africa each reported their third wettest year on record. In Hawaii, 1262 mm precipitation at Waipā Gardens (Kauai) on 14–15 April set a new U.S. record for 24-h precipitation. In Brazil, the city of Belo Horizonte received nearly 75 mm of rain in just 20 minutes, nearly half its monthly average. Globally, fire activity during 2018 was the lowest since the start of the record in 1997, with a combined burned area of about 500 million hectares. This reinforced the long-term downward trend in fire emissions driven by changes in land use in frequently burning savannas. However, wildfires burned 3.5 million hectares across the United States, well above the 2000–10 average of 2.7 million hectares. Combined, U.S. wildfire damages for the 2017 and 2018 wildfire seasons exceeded $40 billion (U.S. dollars)

Soil Moisture-Temperature Coupling in a Set of Land Surface Models

The land surface controls the partitioning of water and energy fluxes and therefore plays a crucial role in the climate system. The coupling between soil moisture and air temperature, in particular, has been shown to affect the severity and occurrence of temperature extremes and heat waves. Here we study soil moisture-temperature coupling in five land surface models, focusing on the terrestrial segment of the coupling in the warm season. All models are run off-line over a common period with identical atmospheric forcing data, in order to allow differences in the results to be attributed to the models' partitioning of energy and water fluxes. Coupling is calculated according to two semiempirical metrics, and results are compared to observational flux tower data. Results show that the locations of the global hot spots of soil moisture-temperature coupling are similar across all models and for both metrics. In agreement with previous studies, these areas are located in transitional climate regimes. The magnitude and local patterns of model coupling, however, can vary considerably. Model coupling fields are compared to tower data, bearing in mind the limitations in the geographical distribution of flux towers and the differences in representative area of models and in situ data. Nevertheless, model coupling correlates in space with the tower-based results (r = 0.5–0.7), with the multimodel mean performing similarly to the best-performing model. Intermodel differences are also found in the evaporative fractions and may relate to errors in model parameterizations and ancillary data of soil and vegetation characteristics

SMOS soil moisture retrievals using the land parameter retrieval model: Evaluation over the Murrumbidgee Catchment, southeast Australia

The land parameter retrieval model (LPRM) is a methodology that retrieves soil moisture from low frequency dual polarized microwave measurements and has been extensively tested on C-, X- and Ku-band frequencies. Its performance on L-band is tested here by using observations from the Soil Moisture and Ocean Salinity (SMOS) satellite. These observations have potential advantages compared to higher frequencies: a low sensitivity to cloud and vegetation contamination, an increased thermal sampling depth and a greater sensitivity to soil moisture fluctuations. These features make it desirable to add SMOS-derived soil moisture retrievals to the existing European Space Agency (ESA) long-term climatological soil moisture data record, to be harmonized with other passive microwave soil moisture estimates from the LPRM. For multi-channel observations, LPRM infers the effective soil temperature (Teff ) from higher frequency channels. This is not possible for a single channel mission like SMOS and therefore two alternative sources for Teff were tested: (1) MERRA-Land and (2) ECMWF numerical weather prediction systems, respectively. SMOS measures brightness temperature at a range of incidence angles, different incidence angle bins (45°, 52.5° and 60°) were tested for both ascending and descending swaths. Three LPRM algorithm parameters were optimized to match remotely sensed soil moisture with ground based observations: the single scattering albedo, roughness and polarization mixing factor. The soil moisture retrievals were optimized and evaluated against ground-based data from the Murrumbidgee Soil Moisture Monitoring Network (OzNet) in southeast Australia. The agreement with single-angle SMOS LPRM retrievals was close to the official SMOS L3 product, provided the three parameters were optimized for the OzNet dataset, with linear correlation of 0.70-0.75 (0.75-0.77 for SMOS L3), root-mean-square error of 0.069-0.085m3 m-3 (0.084-0.106m3 m-3 for SMOS L3) and small bias of -0.02-0.01m3 m-3 (0.03-0.06m3 m-3 for SMOS L3). These results suggest that the LPRM can be applied successfully to single-angle SMOS L-band observations, but further testing is required to determine if the same set of parameters can be used in other geographic areas

Global patterns in base flow index and recession based on streamflow observations from 3394 catchments

Numerous previous studies have constructed models to estimate base flow characteristics from climatic and physiographic characteristics of catchments and applied these to ungauged regions. However, these studies generally used streamflow observations from a relatively small number of catchments (<200) located in small, homogeneous study areas, which may have led to less reliable models with limited applicability elsewhere. Here, we use streamflow observations from a highly heterogeneous set of 3394 catchments (<10,000 km2) worldwide to construct reliable, widely applicable models based on 18 climatic and physiographic characteristics to estimate two important base flow characteristics: (1) the base flow index (BFI), defined as the ratio of long-term mean base flow to total streamflow; and (2) the base flow recession constant (κ), defined as the rate of base flow decay. Regression analysis results revealed that BFI and k were related to several climatic and physiographic characteristics, notably mean annual potential evaporation, mean snow water equivalent depth, and abundance of surface water bodies. Ensembles of artificial neural networks (ANNs; obtained by subsampling the original set of catchments) were trained to estimate the base flow characteristics from climatic and physiographic data. The catchment-scale estimation of the base flow characteristics demonstrated encouraging performance with R2 values of 0.82 for BFI and 0.72 for κ. The connection weights of the trained ANNs indicated that climatic characteristics were more important for estimating κ than BFI. Global maps of estimated BFI and κ were obtained using global climatic and physiographic data as input to the derived models. The resulting global maps are available for free download at http://www.hydrology- amsterdam.nl

CD8(+) T cells characterize early smoking-related airway pathology in patients with asthma

Pathogenesis and treatment of chronic pulmonary disease

Leveraging microwave polarization information for the calibration of a land data assimilation system

This letter contributes a new approach to calibrating a tau-omega radiative transfer model coupled to land surface model output with low-frequency (<10 GHz) microwave brightness temperature (TB) observations. The problem of calibrating this system is generally poorly posed because various parameter combinations may yield indistinguishable (least squares error) results. This is theoretically important for a land data assimilation system since alternative parameter combinations have different impacts on the sensitivity of TB to soil moisture and misattribution of systematic error may therefore disrupt data assimilation system performance. Via synthetic experiments we demonstrate that using TB polarization difference to parameterize vegetation opacity can improve the stability of calibrated soil moisture/TB sensitivities relative to the more typical approach of utilizing ancillary information to estimate vegetation opacity. The proposed approach fully follows from the radiative transfer model, implemented according to commonly adopted assumptions, and reduces by one the number of calibration parameters. Key Points Assimilating microwave observations in land surface model requires calibrationCalibrating with noisy data can bias sensitivity of a radiative transfer modelMicrowave polarization is shown to add beneficial constraints on calibratio