Mid-latitude Land Areas Research Articles

The weather of 1740, the coldest year in central Europe in 600 years

Abstract. The winter of 1739/40 is known as one of the coldest winters in Europe since early instrumental measurements began. Many contemporary sources discuss the cold waves and compare the winter to that of 1708/09. It is less well known that the year 1740 remained cold until August and was again cold in October and that negative temperature anomalies were also found over Eurasia and North America. The 1739/40 cold season over northern mid-latitude land areas was perhaps the coldest in 300 years, and 1740 was the coldest year in central Europe in 600 years. New monthly global climate reconstructions allow us to address this momentous event in greater detail, while daily observations and weather reconstructions give insight into the synoptic situations. Over Europe, we find that the event was initiated by a strong Scandinavian blocking in early January, allowing the advection of continental cold air. From February until June, high pressure dominated over Ireland, arguably associated with frequent eastern Atlantic blocking. This led to cold-air advection from the cold northern North Atlantic. During the summer, cyclonic weather dominated over central Europe, associated with cold and wet air from the Atlantic. The possible role of oceanic influences (El Niño) and external forcings (eruption of Mount Tarumae in 1739) are discussed. While a possible El Niño event might have contributed to the winter cold spells, the eastern Atlantic blocking is arguably unrelated to either El Niño or the volcanic eruption. All in all, the cold year of 1740 marks one of the strongest, arguably unforced excursions in European temperature.

Early 20th century Southern Hemisphere cooling

Abstract. Global surface air temperature increased by ca. 0.5 °C from the 1900s to the mid-1940s, also known as Early 20th Century Warming (ETCW). However, the ETCW started from a particularly cold phase, peaking in 1908–1911. The cold phase was global but more pronounced in the Southern Hemisphere than in the Northern Hemisphere and most pronounced in the Southern Ocean, raising the question of whether uncertainties in the data might play a role. Here we analyse this period based on reanalysis data and reconstructions, complemented with newly digitised ship data from 1903–1916, as well as land observations. The cooling is seen consistently in different data sets, though with some differences. Results suggest that the cooling was related to a La-Niña-like pattern in the Pacific, a cold tropical and subtropical South Atlantic, a cold extratropical South Pacific, and cool southern midlatitude land areas. The Southern Annular Mode was positive, with a strengthened Amundsen–Bellingshausen seas low, although the spread of the data products is considerable. All results point to a real climatic phenomenon as the cause of this anomaly and not a data artefact. Atmospheric model simulations are able to reproduce temperature and pressure patterns, consistent with a real and perhaps ocean-forced signal. Together with two volcanic eruptions just before and after the 1908–1911 period, the early 1900s provided a cold start into the ETCW.

Changes in the mean and variability of temperature and precipitation over global land areas

The frequency and intensity of extreme weather and climate events may change in response to shifts in the mean and variability of climate, which pose high risks to societies and natural ecosystems. Gridded near-surface temperature, precipitation, and the number of wet days from the Climatic Research Unit dataset were analyzed for two 30 year periods to explore changes in the mean and variability of temperature and precipitation over global land areas in the recent period (1991–2020) compared to the reference period (1951–1980). Global land areas are characterized by warmer and slightly wetter conditions in the recent period, while the variability of temperature and precipitation has remained nearly unchanged. Changes in the mean and variability of both temperature and precipitation are also analyzed over tropical, subtropical, and midlatitude land areas. The annual mean temperature over all these three latitudinal regions has increased in the recent period compared to the reference period, with the highest increase in subtropical and midlatitude land areas (0.7 ∘C), followed by tropical land areas (0.5 ∘C), while temperature variability has remained nearly unchanged. The annual precipitation has decreased over tropical, subtropical, and midlatitude land areas in the recent period compared to the reference period. Precipitation variability has not changed considerably over subtropical land areas. However, it has substantially increased over tropical land areas, which indicates a higher risk of droughts and periods of excess water in the recent period. In contrast, precipitation variability has decreased over midlatitude land areas, indicating narrower swings between wet and dry conditions, which decrease the risk of droughts and periods of excess water in the recent period.

Impact of Arctic sea ice variations on winter temperature anomalies in northern hemispheric land areas

Coordinated numerical ensemble experiments with six different state-of-the-art atmosphere models have been used in order to evaluate the respective impact of the observed Arctic sea ice and sea surface temperature (SST) variations on air temperature variations in mid and high latitude land areas. Two sets of experiments have been designed; in the first set (EXP1), observed daily sea ice concentration and SST variations are used as lower boundary forcing over 1982–2014 while in the second set (EXP2) the SST variations are replaced by the daily SST climatology. The observed winter 2 m air temperature (T2m) variations are relatively well reproduced in a number of mid and high latitude land areas in EXP1, with best agreement in southwestern North America and northern Europe. Sea ice variations are important for the interannual T2m variations in northern Europe but have limited impact on all other mid and high latitude land regions. In particular, sea ice variations do not contribute to the observed opposite variations in the Arctic and mid latitude in our model experiments. The spread across ensemble members is large and many ensemble members are required to reproduce the observed T2m variations over northern Europe in our models. The amplitude of T2m anomalies in the coldest observed winters over northern Europe is not reproduced by our multi-model ensemble means. However, the sea ice conditions in these respective winters and mainly the thermodynamic response to the ice anomalies lead to an enhanced likelihood for occurrence of colder than normal winters and extremely cold winters. Still, the main reason for the observed extreme cold winters is internal atmospheric dynamics. The coldest simulated northern European winters in EXP1 and EXP2 between 1982 and 2014 show the same large scale T2m and atmospheric circulation anomaly patterns as the observed coldest winters, indicating that the models are well able to reproduce the processes, which cause these cold anomalies. The results are robust across all six models used in this study.

Multiscale combination of climate model simulations and proxy records over the last millennium

To highlight the compatibility of climate model simulation and proxy reconstruction at different timescales, a timescale separation merging method combining proxy records and climate model simulations is presented. Annual mean surface temperature anomalies for the last millennium (851–2005 AD) at various scales over the land of the Northern Hemisphere were reconstructed with 2° × 2° spatial resolution, using an optimal interpolation (OI) algorithm. All target series were decomposed using an ensemble empirical mode decomposition method followed by power spectral analysis. Four typical components were obtained at inter-annual, decadal, multidecadal, and centennial timescales. A total of 323 temperature-sensitive proxy chronologies were incorporated after screening for each component. By scaling the proxy components using variance matching and applying a localized OI algorithm to all four components point by point, we obtained merged surface temperatures. Independent validation indicates that the most significant improvement was for components at the inter-annual scale, but this became less evident with increasing timescales. In mid-latitude land areas, 10–30% of grids were significantly corrected at the inter-annual scale. By assimilating the proxy records, the merged results reduced the gap in response to volcanic forcing between a pure reconstruction and simulation. Difficulty remained in verifying the centennial information and quantifying corresponding uncertainties, so additional effort should be devoted to this aspect in future research.

Effects of altered precipitation regimes on plant productivity in the arid region of northern China

Climate change scenarios have predicted significant alterations in precipitation patterns over most of the mid-latitude land areas by the end of this century, but the degree to which altered precipitation regimes influence terrestrial ecosystem function in arid regions is uncertain. Precipitation is a primary climatic factor that regulates ecosystem function in arid regions. Based on remote sensing and meteorological data from 2000 to 2013, we analysed the spatiotemporal variations in annual net primary productivity (NPP) for different land cover types in the arid region of northern China and quantified the effects of growing season precipitation (GSP) and seasonal distribution of precipitation (SDP) on NPP variability by using the ecological process Carnegie–Ames–Stanford Approach (CASA) model. Our results suggested that significant NPP increases were found in most of the vegetated areas, especially in grasslands and shrublands. Responses of NPP to precipitation variability were related to land cover types. Grassland and shrubland were most responsive to precipitation variability followed by croplands and forests. Increased precipitation increased NPP, and NPP responded more strongly to higher precipitation than lower precipitation. We also found that increased precipitation concentration decreased NPP. GSP and SDP accounted for approximately 67% and 21%, respectively, of the variability in NPP. We concluded that growing season precipitation and its seasonal distribution were dominant factors controlling inter-annual variability in NPP in the arid region of northern China. Other factors, such as plant functional trait, antecedent soil moisture and human activities, might mediate NPP responses to precipitation variability through interaction with water availability. Our studies have implications for assessing and predicting vegetation responses to future climate change.

Evaluation of CMIP5 upper troposphere and lower stratosphere geopotential height with GPS radio occultation observations

AbstractWe present a detailed comparison of geopotential height fields between the Coupled Model Inter‐Comparison Project phase 5 (CMIP5) models and satellite observations from GPS radio occultation (RO). Our comparison focuses on the annual mean, seasonal cycle, and interannual variability of 200 hPa geopotential height in the years 2002–2008. Using a wide sample of atmosphere‐only model runs (AMIP) from the CMIP5 archive, we find that most models agree well with the observations and weather reanalyses in the tropics in both the annual means and interannual variabilities. However, the agreement is poor over the extratropics with the largest model spreads in the high latitudes and the largest bias in the southern middle to high latitudes that persist all seasons. The models also show excessive seasonal variability over the Northern midlatitude land areas as well as the Southern Ocean but insufficient variability over the tropics and Antarctica. While the underlying causes for the model discrepancies require further analyses, this study demonstrates that global observations from GPS RO provide accurate benchmark‐quality measurements in the upper troposphere and lower stratosphere through which biases in climate models as well as weather reanalyses can be identified.

Effects of Arctic Sea Ice Decline on Weather and Climate: A Review

The areal extent, concentration and thickness of sea ice in the Arctic Ocean and adjacent seas have strongly decreased during the recent decades, but cold, snow-rich winters have been common over mid-latitude land areas since 2005. A review is presented on studies addressing the local and remote effects of the sea ice decline on weather and climate. It is evident that the reduction in sea ice cover has increased the heat flux from the ocean to atmosphere in autumn and early winter. This has locally increased air temperature, moisture, and cloud cover and reduced the static stability in the lower troposphere. Several studies based on observations, atmospheric reanalyses, and model experiments suggest that the sea ice decline, together with increased snow cover in Eurasia, favours circulation patterns resembling the negative phase of the North Atlantic Oscillation and Arctic Oscillation. The suggested large-scale pressure patterns include a high over Eurasia, which favours cold winters in Europe and northeastern Eurasia. A high over the western and a low over the eastern North America have also been suggested, favouring advection of Arctic air masses to North America. Mid-latitude winter weather is, however, affected by several other factors, which generate a large inter-annual variability and often mask the effects of sea ice decline. In addition, the small sample of years with a large sea ice loss makes it difficult to distinguish the effects directly attributable to sea ice conditions. Several studies suggest that, with advancing global warming, cold winters in mid-latitude continents will no longer be common during the second half of the twenty-first century. Recent studies have also suggested causal links between the sea ice decline and summer precipitation in Europe, the Mediterranean, and East Asia.

Low‐frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets

Evidence is presented of a reduction in relative humidity over low‐latitude and midlatitude land areas over a period of about 10 years leading up to 2008, based on monthly anomalies in surface air temperature and humidity from comprehensive European Centre for Medium‐Range Weather Forecasts reanalyses (ERA‐40 and ERA‐Interim) and from Climatic Research Unit and Hadley Centre analyses of monthly station temperature data (CRUTEM3) and synoptic humidity observations (HadCRUH). The data sets agree well for both temperature and humidity variations for periods and places of overlap, although the average warming over land is larger for the fully sampled ERA data than for the spatially and temporally incomplete CRUTEM3 data. Near‐surface specific humidity varies similarly over land and sea, suggesting that the recent reduction in relative humidity over land may be due to limited moisture supply from the oceans, where evaporation has been limited by sea surface temperatures that have not risen in concert with temperatures over land. Continental precipitation from the reanalyses is compared with a new gauge‐based Global Precipitation Climatology Centre (GPCC) data set, with the combined gauge and satellite products of the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC), Merged Analysis of Precipitation (CMAP), and with CPC's independent gauge analysis of precipitation over land (PREC/L). The reanalyses agree best with the new GPCC and latest GPCP data sets, with ERA‐Interim significantly better than ERA‐40 at capturing monthly variability. Shifts over time in the differences among the precipitation data sets make it difficult to assess their longer‐term variations and any link with longer‐term variations in humidity.

Multidecadal changes in near‐global cloud cover and estimated cloud cover radiative forcing

This study examines variability in zonal mean surface‐observed upper‐level (combined midlevel and high‐level) and low‐level cloud cover over land during 1971–1996 and over ocean during 1952–1997. These data were averaged from individual synoptic reports in the Extended Edited Cloud Report Archive (EECRA). Although substantial interdecadal variability is present in the time series, long‐term decreases in upper‐level cloud cover occur over land and ocean at low and middle latitudes in both hemispheres. Near‐global upper‐level cloud cover declined by 1.5%‐sky‐cover over land between 1971 and 1996 and by 1.3%‐sky‐cover over ocean between 1952 and 1997. Consistency between EECRA upper‐level cloud cover anomalies and those from the International Satellite Cloud Climatology Project (ISCCP) during 1984–1997 suggests the surface‐observed trends are real. The reduction in surface‐observed upper‐level cloud cover between the 1980s and 1990s is also consistent with the decadal increase in all‐sky outgoing longwave radiation reported by the Earth Radiation Budget Satellite (ERBS). Discrepancies occur between time series of EECRA and ISCCP low‐level cloud cover due to identified and probable artifacts in satellite and surface cloud data. Radiative effects of surface‐observed cloud cover anomalies, called “cloud cover radiative forcing (CCRF) anomalies,” are estimated based on a linear relationship to climatological cloud radiative forcing per unit cloud cover. Zonal mean estimated longwave CCRF has decreased over most of the globe. Estimated shortwave CCRF has become slightly stronger over northern midlatitude oceans and slightly weaker over northern midlatitude land areas. A long‐term decline in the magnitude of estimated shortwave CCRF occurs over low‐latitude land and ocean, but comparison with ERBS all‐sky reflected shortwave radiation during 1985–1997 suggests this decrease may be underestimated.

Impact of ocean roughness and bogus typhoons on summertime circulation in a wave‐atmosphere coupled regional climate model

In order to examine the impact of ocean roughness and bogus typhoons on the east Asian summer monsoon circulation, three runs with a regional climate model (RegCM2) for 1994 summertime simulation were conducted: a control run (CTRL), a run with RegCM2 coupled to an ocean‐wave model (WAVE), and a run with RegCM2 coupled to a wave model and a bogus typhoon scheme (WBGS). The National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalyses were used for initial and lateral boundary conditions. The regional climate model with a fixed value of roughness length over the ocean (CTRL) did not adequately simulate the extreme anomalous summer monsoon of 1994. However, the simulation of the atmosphere‐wave coupled model (WAVE) produced better anomalous features than CTRL, closer to the 1994 extreme summer climate. In WAVE the roughness length over the ocean was increased to over twice the fixed value. The maximum values of roughness length were found in the active monsoon regions. Increased ocean roughness length resulted in more changes over land rather than over the ocean due to more moisture supplies from the ocean, such that the maximum changes of surface climate occurred over China. In particular, the differences between CTRL and WAVE were relatively large over areas of warmer ground temperature, such as central China. In WBGS the roughness length over the ocean was increased by about 20% relative to that of WAVE under the high wind conditions induced by bogus typhoons. It was also found that the seasonal march of the east Asian summer monsoon was better reproduced in WBGS than in the other two simulations. The bogus typhoons in east Asia played an important role in simulating the variations of surface climate and lower troposphere circulations associated with storms, including typhoons, by the transport of heat and moisture toward the midlatitude land areas. However, the precipitation in WBGS was degraded comparing to that of CTRL. This study suggests that proper simulation of east Asian summer monsoon circulations, especially during an active typhoon season, requires the proper representation of ocean roughness length and typhoons.

The Diurnal Cycle and Its Depiction in the Community Climate System Model

To evaluate the performance of version 2 of the Community Climate System Model (CCSM2) in simulating the diurnal cycle and to diagnose the deficiencies in underlying model physics, 10 years of 3-hourly data from a CCSM2 control run are analyzed for global and large-scale features of diurnal variations in surface air temperature, surface pressure, upper-air winds, cloud amount, and precipitation. The model-simulated diurnal variations are compared with available observations, most of which were derived from 3-hourly synoptic reports and some new results are reported for surface air temperatures. The CCSM2 reproduces most of the large-scale tidal variations in surface pressure and upper-air winds, although it overestimates the diurnal pressure tide by 20%–50% over low-latitude land and underestimates it over most oceans, the Rockies, and other midlatitude land areas. The CCSM2 captures the diurnal amplitude (1°–6°C) and phase [peak at 1400–1600 local solar time (LST)] of surface air temperature over land, but over ocean the amplitude is too small (≤0.2°C). The CCSM2 overestimates the mean total cloud amount by 10%–20% of the sky from ∼15°S to 15°N during both December– January–February (DJF) and June–July–August (JJA) and over northern mid- and high-latitude land areas in DJF, whereas it underestimates the cloud amount by 10%–30% in the subtropics and parts of the midlatitudes. Over the marine stratocumulus regions west to the continents, the diagnostic cloud scheme in the CCSM2 underestimates the mean stratocumulus amount by 10%–30% and does not simulate the observed large diurnal variations (∼3%–10%) in the marine stratocumulus clouds even when driven by observational data. In the CCSM2, warm-season daytime moist convection over land starts prematurely around 0800 LST, about 4 hours too early compared with observations, and plateaus from 1100 to 1800 LST, in contrast to a sharp peak around 1600–1700 LST in observations. The premature initiation of convection prevents convective available potential energy (CAPE) from accumulating in the morning and early afternoon and intense convection from occurring in the mid to late afternoon. As a result of the extended duration of daytime convection over land, the CCSM2 rains too frequently at reduced intensity despite the fairly realistic patterns of rainy days with precipitation >1 mm day−1. Furthermore, the convective versus nonconvective precipitation ratio is too high in the model as deep convection removes atmospheric moisture prematurely. The simulated diurnal cycle of precipitation is too weak over the oceans, especially for convective precipitation. These results suggest that substantial improvements are desirable in the CCSM2 in simulating cloud amount, initiation of warm-season deep convection over land, and in the diurnal cycle in sea surface temperatures.

Cloud liquid water path variations with temperature observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment

Because clouds play such a significant role in climate, understanding their responses to climatic temperature changes is essential to determining the overall impact of a given climate forcing. Cloud liquid water path (LWP) over tropical and midlatitude oceans has been observed to decrease with increasing cloud temperature. The presence of an ice sheet over the Arctic Ocean alters the energy and moisture exchange between the ocean and the atmospheric boundary layer and thus may affect the relationship between LWP and temperature. The variations of LWP with cloud and surface temperatures are examined in this paper using a combination of surface and satellite data taken during the 1998 Surface Heat Budget of the Arctic Ocean and the FIRE Arctic Clouds Experiments. The results show that LWP increases with temperature primarily because of an increase in cloud thickness that is enabled by the rise in surface moisture during the melt season. Cloud base heights and lifting condensation levels decrease as a result of the greater surface relative humidity and temperature. The average change rate of LWP with cloud temperature is 3.3% K−1, a value slightly smaller than earlier observations taken over cold midlatitude land areas. This cloud LWP feedback with temperature differs significantly from that estimated over other marine environments and should be taken into account in all climate models with explicit cloud feedbacks.

Compilation and Discussion of Trends in Severe Storms in the United States: Popular Perception v. Climate Reality

The ongoing greenhouse gas buildup and increase in near-surface air temperatures may have an impact on severe weather events in the United States. Output from some numerical modeling simulations suggests that the atmosphere over mid-latitude land areas could become more unstable in the future thereby supporting an increase in convective activity. However, despite the numerical simulation results, empiricists have been unable generally to identify significant increases in overall severe storm activity as measured in the magnitude and/or frequency of thunderstorms, hail events, tornadoes, hurricanes, and winter storm activity across the United States. There is evidence that heavy precipitation events have increased during the period of historical records, but for many other severe weather categories, the trends have been downward over the past half century. Damage from severe weather has increased over this period, but this upward trend disappears when inflation, population growth, population redistribution, and wealth are taken into account.

Recent Changes in Cloud-Type Frequency and Inferred Increases in Convection over the United States and the Former USSR

Abstract Significant changes and a general redistribution in the frequencies of various cloud types have been observed during the past 40–50 years over the midlatitude land areas of the Northern Hemisphere. This is evident for North America and northern Eurasia in the daytime synoptic data of the United States and the former Soviet Union (FUSSR). An abrupt increase prior to the 1960s largely contributed to the upward trend in the frequency of convective clouds over both regions, particularly in the warm season. However, over both regions during the intermediate seasons and during the winter season over the FUSSR, the frequencies of convective clouds still showed gradual increase after the 1960s. The increase in the frequency of convective clouds has been accompanied by increases in the frequency of observation of high-level cloudiness (at elevations above 6 km) and heavy precipitation. Low cloudiness (stratiform types) has decreased over the FUSSR but increased over the contiguous United States. The latte...

The seasonal cycle in coupled ocean-atmosphere general circulation models

We examine the seasonal cycle of near-surface air temperature simulated by 17 coupled ocean-atmosphere general circulation models participating in the Coupled Model Intercomparison Project (CMIP). Nine of the models use ad hoc “flux adjustment” at the ocean surface to bring model simulations close to observations of the present-day climate. We group flux-adjusted and non-flux-adjusted models separately and examine the behavior of each class. When averaged over all of the flux-adjusted model simulations, near-surface air temperature falls within 2 K of observed values over the oceans. The corresponding average over non-flux-adjusted models shows errors up to ∼6 K in extensive ocean areas. Flux adjustments are not directly applied over land, and near-surface land temperature errors are substantial in the average over flux-adjusted models, which systematically underestimates (by ∼5 K) temperature in areas of elevated terrain. The corresponding average over non-flux-adjusted models forms a similar error pattern (with somewhat increased amplitude) over land. We use the temperature difference between July and January to measure seasonal cycle amplitude. Zonal means of this quantity from the individual flux-adjusted models form a fairly tight cluster (all within ∼30% of the mean) centered on the observed values. The non-flux-adjusted models perform nearly as well at most latitudes. In Southern Ocean mid-latitudes, however, the non-flux-adjusted models overestimate the magnitude of January-minus-July temperature differences by ∼5 K due to an overestimate of summer (January) near-surface temperature. This error is common to five of the eight non-flux-adjusted models. Also, over Northern Hemisphere mid-latitude land areas, zonal mean differences between July and January temperatures simulated by the non-flux-adjusted models show a greater spread (positive and negative) about observed values than results from the flux-adjusted models. Elsewhere, differences between the two classes of models are less obvious. At no latitude is the zonal mean difference between averages over the two classes of models greater than the standard deviation over models. The ability of coupled GCMs to simulate a reasonable seasonal cycle is a necessary condition for confidence in their prediction of long-term climatic changes (such as global warming), but it is not a sufficient condition unless the seasonal cycle and long-term changes involve similar climatic processes. To test this possible connection, we compare seasonal cycle amplitude with equilibrium warming under doubled atmospheric carbon dioxide for the models in our data base. A small but positive correlation exists between these two quantities. This result is predicted by a simple conceptual model of the climate system, and it is consistent with other modeling experience, which indicates that the seasonal cycle depends only weakly on climate sensitivity.

Modelling terrestrial biogenic isoprene fluxes and their potential impact on global chemical species using a coupled LSM–CTM model

In this paper we investigate the important role of the biogenic species isoprene on tropospheric chemistry using a land surface model (LSM) and a three-dimensional (3-D) tropospheric chemistry transport model (CTM). An efficient and conservative coupling scheme is used to couple the LSM to the 3-D CTM. Annual integrations of the coupled model have been performed and the results compared with other estimates. The comparison shows that the annual global isoprene flux from terrestrial vegetation is 530 Tg C yr −1, which is in good agreement with 503 Tg C yr −1 estimated by a high-resolution (0.5°×0.5°) vegetation model of Guenther et al. (1995, Journal of Geophysical Research 100 (D5), 8873–8892). Comparison of the seasonal variations of the surface emission distribution between the coupled model and Guenther et al. (1995) also shows close agreement. The potential impact of isoprene on the levels of tropospheric species is studied by running the same coupled model for the period of June–December but without biogenic isoprene emissions included, and the results are compared with the run which includes biogenic isoprene emissions. Our comparison indicates a significant difference in O 3 and PAN for both hemispheres. The discrepancy between the run with and without isoprene is predominantly governed by the spatial and temporal variations of terrestrial vegetation. The largest difference is seen in the summertime northern hemisphere at locations with extensive terrestrial vegetation (e.g. North America, Europe, east and southeast Asia, South America and equatorial central Africa). For O 3, there is about a 4 ppbv increase over the oceanic areas and about an 8–12 ppbv increase over the mid-latitude land areas. For PAN, a maximum of about one order of magnitude in difference, which increases from 0.01 ppbv (without isoprene emissions) to 0.1–0.3 ppbv (with isoprene emissions), is seen in areas of extensive terrestrial vegetation.

Regional atmospheric angular momentum contributions to polar motion excitation

We focus on a regional analysis of equatorial components of the effective atmospheric angular momentum (EAAM) functions that measure the excitation of polar motion. These functions are computed from National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data both globally and in 108 geographic sectors for the period 1968–1997. We investigate the relationship between the regional sector EAAM and the global functions responsible for polar motion excitation. We examine two excitation terms in parallel, with and without the inverted barometer (IB) approximation, which adjusts the atmosphere to account for an isostatic equilibrium response of the ocean to overlying pressure. In the case of pressure terms without IB the largest contributions to the equatorial components of polar motion excitation functions originate in the South Pacific, North Atlantic, and North Pacific regions. Applying the IB correction results in the dominance of Eurasia and North America instead, with nearly all Southern Hemisphere contributions disappearing. When comparing the regional functions to their global sum, such fluctuations are mainly coherent with variations over northern midlatitude land areas. In some sectors, oscillations in these functions tend to occur broadly across two frequency bands: 25–75 and 75–125 days in both prograde and retrograde directions, corresponding to counterclockwise and clockwise polar motion, respectively. Other sectors contain more continuous spectral bands, which are centered at ∼70 days. Coherence and cross‐spectral analyses lead us to identify a region over Eurasia that contributes importantly to exciting polar motion; we also note an eastwardly propagating signal toward this region in these excitation terms.

A method to derive downwelling longwave fluxes at the Arctic surface from TIROS operational vertical sounder data

The dominant component of the polar surface energy budget during half the year is the downwelling flux of longwave radiation (DLF), yet little is known about its spatial and temporal variability except on monthly timescales. As surface measurements will always be sparse, the most promising opportunity for diagnosing the DLF is provided by satellite data. Estimating this flux from space, however, presents challenges over all surface types and particularly in polar environments where cloud detection and cloud fraction estimation are less certain. A new method is presented to estimate DLF from measurements by the TIROS‐N operational vertical sounder (TOVS). Temperature profiles, humidity estimates, and cloud cover are retrieved from TOVS radiances using the improved initialization inversion algorithm, which has been modified to produce more accurate results over snow and sea ice. This information is combined with brightness temperature differences from pairs of infrared and near‐infrared TOVS channels. These differences are used to infer cloud phase and geometric thickness. Longwave fluxes are then calculated using a forward radiative transfer model. Results during winter 1988 and spring 1992 are compared with hourly radiation measurements from the Coordinated Eastern Arctic Experiment in the eastern Arctic basin and from the Lead Experiment in the Beaufort Sea. Error analyses yield a bias of approximately 3 W m−2, a standard deviation of 23 W m−2, and a correlation coefficient of about 0.75. These errors are comparable to results from similar studies over midlatitude land and ocean areas where clouds are more easily identified.

Geographic analysis of differences in trends between nearsurface and satellite‐based temperature measurements

The purpose of this article is to assess geographical differences that exist in the differential trends between the satellite‐based lower‐tropospheric temperature measurements and the near‐surface temperatures measured by the land and sea thermometer network. Over the period 1979–1994, a highly significant difference of 0.28°C exists between the two global data sets. Analyses presented in this paper show that most of this difference comes from tropical ocean areas, with a much smaller contribution from the mid‐latitude land areas of the Northern Hemisphere. The implications of these results to the many explanations for the differential trend between the data sets are discussed.