<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing with OASIS Tables v3.0 20080202//EN" "journalpub-oasis3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0" article-type="research-article">
  <front>
    <journal-meta><journal-id journal-id-type="publisher">GH</journal-id><journal-title-group>
    <journal-title>Geographica Helvetica</journal-title>
    <abbrev-journal-title abbrev-type="publisher">GH</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Geogr. Helv.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">2194-8798</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/gh-78-87-2023</article-id><title-group><article-title>Sensing weather: scientific and experiential modes of knowledge production for small-scale <?xmltex \hack{\break}?> farming in western Kenya</article-title><alt-title>Sensing weather: scientific and experiential modes of knowledge production</alt-title>
      </title-group><?xmltex \runningtitle{Sensing weather: scientific and experiential modes of knowledge production}?><?xmltex \runningauthor{J. Rochlitz}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name><surname>Rochlitz</surname><given-names>Julian</given-names></name>
          <email>julian.rochlitz@gmail.com</email>
        </contrib>
        <aff id="aff1"><institution>independent researcher: Germany</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Julian Rochlitz (julian.rochlitz@gmail.com)</corresp></author-notes><pub-date><day>21</day><month>February</month><year>2023</year></pub-date>
      
      <volume>78</volume>
      <issue>1</issue>
      <fpage>87</fpage><lpage>98</lpage>
      <history>
        <date date-type="received"><day>9</day><month>December</month><year>2021</year></date>
           <date date-type="rev-recd"><day>2</day><month>January</month><year>2023</year></date>
           <date date-type="accepted"><day>13</day><month>January</month><year>2023</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2023 Julian Rochlitz</copyright-statement>
        <copyright-year>2023</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://gh.copernicus.org/articles/78/87/2023/gh-78-87-2023.html">This article is available from https://gh.copernicus.org/articles/78/87/2023/gh-78-87-2023.html</self-uri><self-uri xlink:href="https://gh.copernicus.org/articles/78/87/2023/gh-78-87-2023.pdf">The full text article is available as a PDF file from https://gh.copernicus.org/articles/78/87/2023/gh-78-87-2023.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d1e77">Agriculture depends in large part on relations with weather
phenomena, such as rain and temperature. Anticipatory knowledge about the
atmosphere therefore is vital in agricultural livelihoods. Based on an
ethnographic case study of weather forecasting for small-scale farming in
western Kenya, in this paper I discuss different ways in which knowledge
about the future weather is produced. While development organizations
promote expert forecasts that draw on meteorological sensing technologies as
a solution to dealing with climate change, I show how knowing the weather is
an entangled affair in a sensory assemblage that simultaneously draws on
scientific instruments and on other entities such as animals, plants,
clouds and embodied sensoria associated with experiential knowledge.
Building on concepts related to science and technology studies that address
the relations between humans and nonhumans, I suggest to treat scientific
and experiential devices symmetrically by looking at their more-than-human
sensoria, proxies and imaginations to understand how farmers attune to the
weather. In practice, then, navigating the uncertainties of the weather is
not enabled by scientific meteorology alone, but by combining different
sensory devices and practices of interpretation that together mediate the
weather as something to be known and acted upon.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e89">“A good farmer has to know the weather. If someone is not interested in the
weather, that person is not a farmer” (field notes, 29 November 2017). As this
statement shows, an understanding of the weather is considered crucial both
for the success of farming and farmers' identities. However, impacts of
climate change such as increased frequency of extreme occurrences and of
overall climate variability seem to make anticipating the weather more
difficult for farmers (Ouma et al., 2013). To meet the resulting challenges
both for Kenya's food security and for its economy, to which rain-fed
agriculture is a major contributor, suggestions have been made to improve
the distribution of climate information to farmers (Government of Kenya,
2010). One particular channel to circulate such information that has been
identified as promising for its potentially wide reach and low cost is the
dissemination through mobile phones (e.g., Caine et al., 2018).</p>
      <p id="d1e92"><?xmltex \hack{\newpage}?>In this paper, I discuss the relations of different ways of producing
environmental knowledge pertaining to “climate information” for farmers. I
particularly draw on the case of a project that, following the above
argumentation, aims to spread weather forecasts through SMSs to small-scale
farmers in western Kenya, a major production region of Kenya's main staple
crop, maize. While rural populations in this region have a rich tradition of
experiential forecasting (Ouma et al., 2013; Gumo, 2017), this project
assumed that experiential knowledge of the weather was stable and unable to
navigate change and that responses to this demand scientific knowledge.</p>
      <p id="d1e96">This view of scientific and experience-based approaches has been a common
feature of development interventions, which often embrace technologies and
repertoires of knowledge that are perceived as more modern. Interventions
that concern natural environments commonly have been studied through the
lens of political ecology. Traditionally employing a historical-materialist
perspective, it critically engages<?pagebreak page88?> with access to resources and related
question of power and control (Goldman and Turner, 2011). While this
perspective has merit for addressing uneven distributions of natural
resources and the power-laden relations of social actors, recent literature
informed by science and technology studies (STS) has pointed to some
shortcomings and necessary additions.</p>
      <p id="d1e99">Two of these are important here. First, Bauriedl (2016) not only calls for a
stronger focus on postcolonial perspectives but also for decentering the
human as knowing actor – an argument that follows concepts of agency as
coproduced in hybrid networks, which have been prominent in STS especially
through the works of Latour (2014, 2007). Second, knowledge and expertise
should not be treated as “blackboxes” that can be used and transferred
equivalent to a resource. Instead, STS suggests to explore how knowledge is
produced and contested in specific contexts involving humans and nonhumans
(Whatmore, 2014; Goldman and Turner, 2011). Discussing multiple ways of
knowing, both assumptions about the dominance of science and uncritical
beliefs in technocratic solutions can be avoided (Watts and Scales, 2015).</p>
      <p id="d1e103">Instead, this understanding allows us to explore how science and technology
are mobilized in the name of development and how accepted (or contested)
knowledge about reality comes to be in and through social, technical and
material relations. Focusing on how weather is sensed and made sense of,
this paper attends to the “plurality of sensing practices, together with
the expanded environmental collectives that are involved in sensing”
(Gabrys, 2019: 725). It specifically asks how knowledge about the weather is
produced in multiple forecasting practices informing smallholder agriculture
in western Kenya. Subquestions are how these forms of knowledge can be
understood more symmetrically and how they relate in farmers' activities.</p>
      <p id="d1e106">To answer these questions, I will proceed as follows. In Sect. 2 I will
explain the different modes and stakes of knowing the weather in the case of
an information service for small-scale farmers in western Kenya and outline
my methodology researching it. In Sect. 3, I will develop the conceptual
grounds to move beyond essentialist separations between scientific and
non-scientific knowledge. In Sect. 4 I will present some insights from my
fieldwork to show symmetries among scientific and expert ways of sensing
weather, particularly paying attention to their more-than-human sensoria,
proxies, as well as the images and imaginations they make use of. On that
basis, in Sect. 5, I show how experiential and scientific modes of knowing
the weather are connected in various and distinct ways. In Sect. 6 I
finally offer some concluding remarks on how people inhabit their
environments through multiple ways of knowing and the implications for
development interventions.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Farming and modes of anticipating the weather</title>
      <p id="d1e117">Recognizing the general importance of the weather for agriculture is not new,
and there have been well-documented historical connections between farming
and weather forecasts, both through applications of folk knowledge (e.g.,
Taylor, 2013 [1812]) and as an early driver in the development of scientific
meteorology (c.f. Harper, 2008). This importance of weather knowledge is
also evident in small-scale agriculture in Kenya. Here it is exacerbated by
climate change leading to higher variability, increased occurrences of
weather extremes and, overall, a reduced reliability of weather patterns
(Ouma et al., 2013). This presents major challenges for the mostly rain-fed
farming in western Kenya, which is a main agricultural production area in
the country. According to FAO's (2021) crop calendars, in the (sub)humid
mid-elevation areas of western Kenya the main staple crop maize can be
planted from early to mid-March and harvested from August through September with
a subsequent second planting from August/September. However, conversations
with farmers and experts in agricultural organizations suggest that these
periods can no longer be fully relied upon. For example, during October 2017
farmers in Trans Nzoia were waiting for unusually lasting rains to
cease in order to harvest.</p>
      <p id="d1e120">To address these challenges, one project that I focus on in this paper was
initiated in 2016 to develop a system in which farmers in nine counties in
western Kenya receive weekly weather forecasts as SMS messages. To implement
this, the Kenya Meteorological Department (KMD) collaborated with
international and local NGOs that already had an established outreach to
farmers. KMD's meteorologists in the involved counties produced seasonal,
monthly and weekly forecasts for the agroclimatic zones in their area and
sent them to those organizations. They sent them as text messages (Fig. 1) to key individuals such as farmer group leaders and extension workers who
passed on the information to farmers they worked with.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><?xmltex \currentcnt{1}?><?xmltex \def\figurename{Figure}?><label>Figure 1</label><caption><p id="d1e125">Example of weather forecast message.</p></caption>
        <?xmltex \igopts{width=199.169291pt}?><graphic xlink:href="https://gh.copernicus.org/articles/78/87/2023/gh-78-87-2023-f01.png"/>

      </fig>

      <p id="d1e135">Asking one of these meteorologists about how the forecasts that inform such
messages are produced, he asserted, “this is purely scientific, you have to
be a meteorologist” (interview, 24 October 2017). On another occasion, one of
his colleagues explained that “weather forecasting involves the collection
of data, past and present data, and then you use assumptions of physical
processes in the atmosphere to determine, really determine the future, the
future weather” (interview, 14 November 2017). The meteorologists<?pagebreak page89?> further
explained that the products they use as a basis for their forecasts are
numerical weather prediction products. Based on physics and mathematical
modeling, these have been the main technique of weather forecasting since
the 1950s and are closely linked to the wider rise of computer-based
modeling in the sciences (Harper, 2008). Equipped with the authority of
science and particularly calculative techniques, the meteorologists cited
above therefore are certain to provide farmers with determinate information
on the future weather.</p>
      <p id="d1e138">This, however, is not the only kind of information farmers targeted by the
climate information project are exposed to. Indeed, alternative forecasting
practices are common among rural communities in Kenya. For example, in late
2017 a farmer called Richard who lives near Kakamega told me this:</p>
      <p id="d1e141"><disp-quote>
  <p id="d1e144">When the climate changes, I just use my own information. You can detect
the climate on your own. <inline-formula><mml:math id="M1" display="inline"><mml:mi mathvariant="normal">…</mml:mi></mml:math></inline-formula> For example, when the dry season is
coming, insects [butterflies] migrate to places where the sun does not hit.
They will move from dry land to the forest, because they assume that the
forest is not dry. When it gets cold, when the rainy season is coming, they
move out.</p>
</disp-quote></p>
      <p id="d1e155">Intrigued by this method of detection, which he called cultural, I tried to
put his knowledge to the test and asked him what the weather would be like
in the days to come. He replied:</p>
      <p id="d1e158"><disp-quote>
  <p id="d1e161">“we might have showers for two to three days from now on to the 12th.
Before the 12th, we'll have some minimal rain, maybe not continuous”. I
asked him what told him and he said, “the owl. Usually, when it expects
continuous rain it comes out of the forest, and when it expects heavy
downpours, or heavy rain, it goes to the edge of the forest and out of the
forest”. And this time, he said, the owl had appeared and then vanished
back inside the forest. Therefore, he expected just showers and minimal
rain. He also noted that “it's hard to see the owl. You have to be patient.
You can't really see it, but you can hear it”. (excerpts from field notes,
7 December 2017)</p>
</disp-quote></p>
      <p id="d1e165">Here, knowing the weather involves a different set of entities to be
observed and other interpretative techniques in order to determine future
states of the atmosphere. Calls to conceptualize weather knowledge from the
perspective of its users and to recognize non-scientific knowledge have
especially been voiced with regards to often marginalized rural communities
in the Global South, including Ethiopian pastoralists (Balehegn et al.,
2019; Iticha and Husen, 2019), as well as farmers in northern Ghana (Nyadzi
et al., 2021), southern Uganda (Orlove et al., 2010) and various
communities in Kenya (Ouma et al., 2013; Vervoort et al., 2016). Although
not challenging scientific knowledge per se, Rice et al. (2015) more explicitly
critique the hegemonic knowledge politics of those sciences that marginalize
other ways of knowing.</p>
      <p id="d1e169">While developing a critical perspective on the dominance of science and
recognizing other forms of knowing are important, it is also necessary to
understand how different knowledges of the weather are produced in specific
practices, how they may be understood more symmetrically and what their
relations are in people's lives. The conceptual approach that informs these
questions and the methodology used to answer them draws on insights from
STS, which has pointed to the hybridity of actors and mutual constitution of
humans and nonhuman beings (Whatmore, 2006; Latour, 1993). Crucially, it
has also highlighted the ways in which (scientific) knowledge is not a
mirror image of reality but is constructed in hybrid networks of
researchers, instruments, interpretative techniques and academic
institutions (e.g., Latour, 1987).</p>
      <p id="d1e172">Especially applying Latour's (2007) take on actor network theory to the
production of both scientific and experiential knowledge provides a useful
mode of researching by tracing the associations that make up those networks
and through which knowledge is produced and disseminated. Thus following
actors and knowledge through their networks, this research took the form of
a multi-site ethnography (Hannerz, 2003). Focusing on two of the counties
targeted by the weather forecast project introduced above, Trans Nzoia and
Kakamega, these sites included small-scale farms, agricultural training
sites, weather stations, and the offices of NGOs working for agrarian and
rural development. Applying an ethnographic approach to the use of
information technologies in the production and use of environmental
knowledge can be understood as “technography” (Kien, 2008; Jansen
and Vellema, 2011). Research included recurrent periods of participant
observations with farmers and field officers employed by NGOs between
October 2017 and April 2018. During this time and during a later period in
March and April 2019, I conducted a total of 43 qualitative interviews.
These comprised 24 interviews with farmers, 8 with meteorologists, 8 with
staff of NGOs and 3 with voluntary rainfall observers. In addition, I
conducted 7 group discussions with farmers and farmer group leaders. For the
purposes of this paper, all individual names of research participants were
anonymized.</p>
      <p id="d1e175">Before presenting empirical insights from this research, in the next section
I will outline in more detail the conceptual basis on which I problematize
essentialist and dichotomical understandings of scientific and
non-scientific forms of environmental knowledge and argue for an alternative
conceptualization.</p>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>From epistemological binaries to attuned sensing</title>
      <p id="d1e186">While acknowledging the plurality of knowledge practices and the value of
non-scientific knowledge is important, it is in itself insufficient to
overcome essentialist<?pagebreak page90?> conceptualizations. Despite having relied on their own
experience with the weather, such thinking is not uncommon even among some
farmers:</p>
      <p id="d1e189"><disp-quote>
  <p id="d1e192">As one woman in a western Kenyan village said, “we looked at the clouds and
we would try to imagine that there will be rain”. <inline-formula><mml:math id="M2" display="inline"><mml:mi mathvariant="normal">…</mml:mi></mml:math></inline-formula> Her
husband explained, “in Kiswahili-speaking countries we have a saying, which
is `dalili ya mvua ni mawingu', the sign for rain is clouds. For a long
time, we used this, but scientifically clouds do not necessarily mean rain;
the assumption has been overtaken by knowledge and events”. (excerpt from
field notes, 28 November 2017)</p>
</disp-quote></p>
      <p id="d1e203">Evident here is a thinking that upholds a categorical distinction between
scientific and non-scientific knowledge to an extent that only science is
considered knowledge at all, while observations and experience are assigned
a status of mere assumptions. Such claims of essential difference often are
made along substantive, epistemological and contextual lines (Agrawal,
1995). Along these lines, scientific knowledge is based on abstract
philosophies, is presumed to be neutral, produced in an analytical,
systematic and objective way and makes universalist claims about reality. On
the other hand, so-called indigenous knowledge is based on an intimate
connection with livelihoods, is based on common sense, is non-systematic,
non-objective and closely linked to its context of application.</p>
      <p id="d1e206">While this hierarchical understanding of scientific and non-scientific
knowledge seems persistent, work in STS warrants a move beyond such a
conceptualization, asking how and under which conditions environmental
knowledge is produced, circulated and used (Goldman and Turner, 2011). This
starts with a general perspective on scientific knowledge as the outcome of
a set of practices that hinge on large networks of institutions and
instruments (Latour, 1987). While not implying a criticism of scientific
knowledge as such, this is indeed a critique of powerful, authoritative
claims of science (Latour, 2013). Similarly, studies on environmental
sensing have pointed to the power of (scientific) data in environmental
management and related decision-making processes (Adams, 2020; Gabrys,
2016b). Selectively privileging certain objects of study and possibilities
of interpretation, environmental data practices not only beg epistemological
but also normative questions (Gabrys, 2016a).</p>
      <p id="d1e210">This epistemological power contrasts with a plurality of non-academic ways
of knowing the world that inform people's lives as much and that may
involve affect, embodiment, situatedness and performativity (Law, 2016). In
addition, Coté (2010) challenges hierarchical relations between
<italic>episteme</italic> (abstract knowledge) and <italic>techné</italic> (practical knowledge) by arguing that not only
scientific knowledge but also embodied experience and the human sensorium
are always already mediated. In turn, Ballestero (2019) traces how embodied
senses are turned into conceptual resources in scientific practices, arguing
for an attention to sensorial combinations. In other words, presumably
abstract science also has embodiment, and ostensibly direct, embodied
experiential sensing also accesses the world in a mediated way.</p>
      <p id="d1e219">Deconstructing categorical distinctions between scientific and indigenous
knowledge, Agrawal (1995) makes two points. First, indigenous knowledge and
scientific knowledge are in themselves heterogeneous and may share elements
among each other. Second, both indigenous and scientific knowledge are
dynamic and have been in contact with each other for centuries, often
rendering it impossible to clearly separate them. One attempt to relate
traditional weather forecasting with science is made by Kenyan climate
scientists, who try to “harmonize” their predictions with those of Nganyi
indigenous forecasters and develop an agreement among the two groups (Ouma
et al., 2013). However, by “demystifying” indigenous knowledge, they stay
within the scientific perspective, implicitly setting it as the norm of
knowing. As a consequence, explaining indicators used by indigenous
forecasters through science would ultimately make considerations of
indigenous forecasting obsolete, because it presumably could be fully
explained by science. Similarly, Iticha and Husen (2019) have attempted to
integrate scientific and indigenous forecasting among Borana pastoralists in
Ethiopia, and Nyadzi et al. (2021) have tried to compare indigenous
forecasting with scientific meteorology in a quantitative assessment of
their respective success in actually predicting the weather.</p>
      <p id="d1e222">While these comparative approaches can be useful in recognizing the value of
non-scientific forecasting methods, they lack an engagement with how
different knowledge practices relate in ordinary people's everyday
activities. This has been addressed by Balehegn et al. (2019) who show that
Afar pastoralists do not use a single indicator to predict weather but draw
information from a wide variety of sources, both traditional and scientific.
Similarly, Vervoort et al. (2016) demonstrate how farmers in Kenyan
communities use weather information flexibly, drawing on several local and
external sources in agricultural decision-making. As Orlove et al. (2010)
point out in their study of indigenous climate knowledge among farmers in
southern Uganda, farmers are not only consumers of weather information but also
share their experiential knowledge to actively engage as producers in
programs that draw on climate science for climate change adaptation. These
examples show the importance of both scientific and experiential knowledge.
Adding to this, I argue that it is important to develop a better conceptual
understanding of the ways in which they are produced in practice, how they
can be understood more symmetrically and in which ways they become
entangled in what Vervoort et al. (2016) call farmers' “working
knowledge”.</p>
      <p id="d1e225">To think of sensing and making sense of the weather in non-essentialist
ways, I seek to understand how scientific and experiential forms of
knowledge are produced and how they<?pagebreak page91?> relate by considering how people attune
to the weather. Generally, attunement refers to practices and processes
through which people form relations with the environments they care about
and/or that are vital for them. While the term has originally been used to
conceptualize humans' relations with animals (Despret, 2004), more recently
it has been employed to think through people's engagement and the knowledges
related to the atmosphere, e.g., controversies concerning air quality (Calvillo,
2018) and ways of knowing climate change (Howe, 2019). Considering the
production of knowledge, thinking in terms of attunement rejects the
possibility of universal and distanced knowledge and instead points to
situated practices of noticing described by Tsing (2015, 2017). In this
vein, it assumes a fundamental impossibility of unmediated and complete
knowledge and instead enables – always incomplete – knowledge in “a living,
dynamic relation” (Morton, 2018: 89). With regards to farming in western
Kenya, the concept therefore raises questions about how farmers relate to
the weather, an environmental factor that vitally and intimately concerns
them, by drawing on various imperfect knowledges and applying them in their
everyday contexts.</p>
      <p id="d1e228">In the following section, I will discuss three aspects through which farmers attune to weather, both with scientifically produced and experiential knowledge. First, sensoria will be discussed. These are the more-than-human devices and capacities through which phenomena are registered, including technological devices, but also embodied senses of humans, animals and plants. The second aspect is what I call proxies. Here, I use the term in the sense of Rice et al. (2015) when they speak of the way in which climate change is detected through observations of landscape change and personal memories. In this understanding, proxies are the mediators that stand in for weather processes, e.g., indicators, measurements and data, as well as the behavior of animals, trees, plants, clouds, etc. The third aspect consists of images and imaginations, or in other words “models”, through which weather is made sense of. This includes cultural beliefs, as well as theoretical assumptions, through which meaning is given to what sensoria “tell” by providing observable proxies for future weather.</p>
</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Symmetries: imagining weather through more-than-human proxies and sensoria</title>
      <p id="d1e239">In order to develop a fuller understanding of how weather comes to be known,
in this section I will discuss how scientific and experiential practices can
be understood symmetrically by exploring the sensoria, proxies and models
that together make weather knowledge. This means to not assume foundational
differences between their respective sensing devices and practices, the
environmental indicators they observe, and their models of the world. As
will become clear, they all use proxies and none has direct access to the
world they seek to know. Also, all their sensoria can be understood as
more-than-human and all use models, imaginations and images.</p>
<sec id="Ch1.S4.SS1">
  <label>4.1</label><title>Experiential proxies and sensoria</title>
      <p id="d1e249">Reconsidering the example of experiential knowledge I quoted above, Richard
observed butterflies that migrate in and out of the forest when it is hot
and cold, respectively. In addition, he observed the behavior of an owl also
in relation to the forest. In the course of our conversation, he further
recounted how he also observes snakes to know the advent of cooler rainy
weather and hotter dry spells (field notes, 7 December 2017).</p>
      <p id="d1e252">I received similar accounts from various farmers and groups of farmers
throughout the time I spent in western Kenya. For example, in early 2018 I
accompanied a field officer of an agricultural NGO to a meeting with a group
of farmers in Trans Nzoia, where I also had a conversation with the
farmers about how they use and produce knowledge about the weather. These
farmers get expert forecasts from meteorologists but experiential methods of
knowing the weather, which they report having acquired from their ancestors,
are still relevant to them. Similar to Richard, these farmers observe birds:
when a specific kind of black and white bird is seen flocking in groups, they
said that was a sign for coming rain. Other indications of rain are
observations of clouds and lightning, heat at night, frogs croaking at night,
and the wind blowing from east to west. In addition, the onset of seasonal
rains is expected when a type of ant, called the safari ant, enters the house at
a particular time of the year, when butterflies can be seen in groups flying
from east to west, when morning dew is observed when it is cold in the
morning and when the leaves start regenerating in some family of trees that
shed their leaves in the dry season (field notes, 8 February 2018).</p>
      <p id="d1e255">This list shows the multiple relations that people engage in to know the
weather. These are relations with living and non-living entities, which I
understand as proxies, because people use them as entities that tell
something about the weather. These are in part multispecies proxies: to know
the weather, people enact relations with multiple living beings such as
birds, butterflies, trees and forests. However, experiential knowledge is
not limited to multispecies proxies and multispecies relations. Since people
do not only observe living organisms but also other phenomena such as
lightning, clouds and physical indications of wind direction, they truly
engage multiple entities that can be understood as more-than-human proxies,
including other beings that “stand in” for the weather.</p>
      <p id="d1e258">As a consequence, not only the proxies but also the sensoria of
experiential knowledge are more-than-human. To clarify the difference,
proxies in the sense of Rice et al. (2015) can be understood as standing in
for the weather, like indicators and measurements, but also the behavior of
animals, plants and trees. In contrast, I understand sensoria as the devices
and capacities through which phenomena are sensed<?pagebreak page92?> and registered. Briefly
then, the more-than-human sensoria are the entities themselves, while
proxies are what they show in their behavior. That said, experiential
knowledge draws on embodied sensoria in multiple ways. On the one hand these
are human embodied senses when people feel heat, cold or humidity, when they
see clouds, wind direction, the visibility of the sky and other
environmental indications, and when they hear, see and feel what animals and
plants do. But those sensoria are not only human precisely because they in
part draw on what animals and plants themselves sense and how they react to
environmental processes and dynamics. For example, in some tree species
flowering or the shedding of leaves can indicate changes in humidity before
humans might be able to sense them, and some ant species are known to leave
their nests before rain sets in to protect themselves from drowning
(Ouma et al., 2013). Engaging in such multispecies relations therefore
makes experiential sensing a more-than-human affair.</p>
      <p id="d1e262">Observing, feeling and hearing all those entities and accessing them with a
full human sensorium then means to use them similar to sensing devices. In a
certain way, people “read” ants, trees, butterflies, birds and all the
other entities that they observe in a composite way. Only by taking all those
“readings” together, can people draw conclusions about what to anticipate.
In a similar way, scientific meteorology also uses proxies to register
phenomena that say something about the weather, which can be understood as
more-than-human sensoria as well.</p>
</sec>
<sec id="Ch1.S4.SS2">
  <label>4.2</label><title>Scientific sensoria and proxies</title>
      <p id="d1e273">While the immediate purpose of data produced by meteorologists in Kenya is
not to produce locally tailored weather forecasts for farmers, they still
play a role in those predictions, however in a more indirect and mediated
way. Generally, data produced in Kenyan weather stations are fed into national
and international databases and inform weather prediction products on
various spatial scales and in various institutional settings. Such
prediction products are important for a general consideration of how
scientific meteorology produces its knowledge about future states of the
atmosphere. Since Kenyan meteorologists widely use them, they are also
relevant to understand how localized forecasts are produced.</p>
      <p id="d1e276">Here, I draw on some accounts that I experienced during my research in
Kenya. Not having discussed remote sensing technologies, this is not a
comprehensive account of all sensing practices used in meteorology.
Nonetheless, it provides insights specifically into the sensing practices of
Kenyan meteorologists that also form a part of the production of global
weather data. During a visit to the weather station in Kitale, the lead
meteorologist based there showed me around the plot with weather data
collection devices. These included automatic and semi-automatic rain gauges,
thermometers, hygrometers to measure humidity, and anemometers for wind
speed and direction, which are in different ways susceptible to registering
atmospheric phenomena. For example, the meteorologist demonstrated to me the
functioning of a rain gauge. On opening it, he revealed a mechanism with two
buckets that are balanced on a tipping point (similar to a scale) and
explained that the two buckets of equal size can hold the same amounts of
water. Rain water is channeled into one of the buckets until it contains a
defined amount of water. It then tips over and water fills the other bucket
until that contains the same amount of water, and the process repeats. At
each time the buckets tip over, the rain gauge takes a reading, and the
amounts of rainfall can be determined by counting how many times they have
tipped over a certain period (field notes, 30 October 2017). In a simpler way,
the meteorologists in Kitale also engaged voluntary rainfall observers whom
they provided with simple rain gauges. Here, water collects in a bottle,
which on a daily basis is emptied into a measuring cup, and the collected
rainfall amount is documented on paper in a tabular form (interviews,
22–23 March 2019).</p>
      <p id="d1e279">As is the case with experiential sensoria, these scientific instruments can
be understood as more-than-human. While they do not consist of living beings
or environmental phenomena, scientific sensing equally has no direct access
to the weather but uses an extended array of entities to register
atmospheric phenomena. This does not imply that they are the same and there
remain noteworthy differences. Importantly, on the one hand, technical
devices are designed for a specific purpose. On the other hand, the entities
drawn on in experiential knowledge practices are not designed to know the
weather. However, it is not only important to note the ways in which they
are made and the purposes they are made for (if they can be said to be
“made” at all, which usually does not apply to living beings like animals
and plants) but also to understand the purposes they are assigned and the ways
they are related to by people in order to know the weather.</p>
      <p id="d1e282">This more-than-human character not only applies to the sensorial devices
through which weather is detected but also to the data and indicators that
they express about rainfall amounts, humidity, temperature, wind, air
pressure and others. For example, voluntary rainfall observers note their
readings on a standardized sheet documenting the amounts of rainfall they
have collected in millimeters for each day of the month. These sheets
eventually are collected by the meteorologists and sent to a national
repository. Of course, data are also collected in meteorological weather
stations. Here, some devices work automatically, feeding their readings into
a digital database in an automated way. Other readings have to be taken
periodically by hand, or they have to be copied into digital form. For
example, some rain gauges mark readings on a rotating slip of paper and
trained staff have to copy their readings into a digital form for further
processing (field notes, 30 October 2017). As meteorologists indicated, such
data are then sent to databases and computing centers at the national
headquarters in Nairobi and further to the World Meteorological Organization
(WMO) where they are fed into and inform national and global weather prediction
products.</p>
      <?pagebreak page93?><p id="d1e286"><?xmltex \hack{\newpage}?>Here, too, knowledge about the weather is derived from skillful readings of
sensory devices. This is in line with long-standing insights from STS that
have pointed to the role played by technical instruments and observational
choices through which scientific knowledge is constructed (Latour, 1987). As
is seen here, nonhuman sensoria and related proxies are crucial to make
statements about the future weather both in meteorology and experiential
knowledge practices.</p>
</sec>
<sec id="Ch1.S4.SS3">
  <label>4.3</label><title>Imagining weather</title>
      <p id="d1e298">Sensing and knowing the weather does not only entail sensoria and proxies.
Both modes of knowledge additionally hinge on imaginations and models of the
world. For example, when I interviewed Mary and Isaac, a married couple of
farmers living near Kakamega, Isaac remarked that before they got the weather
forecasts, they “just used imagination”. Mary continued, “we used the
<italic>kienyeji</italic> [Swahili for traditional, indigenous, local] one, the natural one. It's a
belief from the ancestors. We see the clouds this side or that side in the
morning or the evening and the wind direction. But the present one is a bit
correct. When it says it doesn't rain, it doesn't rain. Like this week, if
you use this cloud, there were clouds but no rain”. So the natural one, as
she called it, is not accurate: “you plant crops, you plant and the crops
will disappear. It's wrong most of the time” (interview, 29 November 2017).</p>
      <p id="d1e304">In this account it is noteworthy that the couple describes the traditional
and experiential ways of knowing the weather in terms of imagination and
beliefs, which in their view is opposed to knowledge. They particularly talk
of imagination in a sense that denounces the validity of statements derived
from it, arguing that scientific forecasts are more accurate. This implies
that to use experiential ways of forecasting, one has to believe in them. In
addition, when Isaac talks about imagination, he implies that this is
something fictitious, not based in reality. However, the notion of
“imagination” may be adequate to understand both experiential and
scientific ways of knowing if we consider it being rooted in images, not
only referring to visual depictions but also more generally to a “bigger
picture”. Reinterpreted in this way, speaking of imagination alludes to the
models of the world and the techniques through which observations become
meaningful in reference to existing rules in already established systems of
knowledge that, in the case of experiential knowledge, have conventionally
been understood as “cultural” (Gumo, 2017; Ouma et al., 2013).</p>
      <p id="d1e307">Talking about different modes of the weather symmetrically then means to ask
in turn what are the imaginations, images and models that are used by
scientific meteorology, too? Notably, when the meteorologist quoted in Sect.
2 explained that weather forecasting hinges on “assumptions of physical
processes in the atmosphere” (interview, 14 November 2017), it becomes clear
that scientific knowledge, too, is shaped by prefigured concepts about how
the atmosphere behaves. Another meteorologist talked about how it is
necessary to tune models: when he tries to make predictions about the
weather in his area he uses models that relate to larger spatial scales. He
further explained that, in order to give correct predictions for his smaller
geographical area, he has to do what he called “tuning”: “you have to
filter and remove model errors <inline-formula><mml:math id="M3" display="inline"><mml:mi mathvariant="normal">…</mml:mi></mml:math></inline-formula> and there is a way of doing it.
For example, I know where Lake Victoria is, and with time you realize if you
have an easterly or westerly wind; in this particular month the model is
underestimating or overestimating the rain. So you tune it” (interview,
24 October 2017, paraphrased).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><?xmltex \def\figurename{Figure}?><label>Figure 2</label><caption><p id="d1e320">Examples of visual forecast products used by Kenyan meteorologists
(photo taken by the author, 2 April 2019).</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://gh.copernicus.org/articles/78/87/2023/gh-78-87-2023-f02.jpg"/>

        </fig>

      <p id="d1e329">This need to “tune” models based on his experience and data series of the
local climate shows that, despite universal claims, scientific knowledge
does not provide immediate descriptions of reality but hinges on
context-dependent interpretative practices (Agrawal, 1995). As Morton (2018)
argues, reality can never be known directly and completely. Hence, there is
always a gap between the world and the models through which it is known.
Similarly, just as imaginations and beliefs are said to make (up) the world, Edwards (2001) understands atmospheric modeling as a practice of world-making rather than one that precisely describes present and future
realities. Looking at the outputs of such models, which often are visual
depictions in the form of maps (Fig. 2), it can be argued that they have
imaginary qualities: like the models of the world that inform experiential
knowledge, they enable their users to imagine future states of the
atmosphere and to act on this basis.</p>
</sec>
</sec>
<sec id="Ch1.S5">
  <label>5</label><title>Entanglements of scientific and experiential knowledge in practice</title>
      <p id="d1e342">Scientific meteorology and experiential weather forecasting cannot only be
understood symmetrically. In farmers' practices, they are indeed entangled.
This means that distinctions between science and experiential knowledge are
challenged not only by conceptualizing attunements to weather through
sensoria, proxies and the imaginative qualities of models but also by what
farmers do in their everyday activities. Here, I identify three kinds of
entanglement between those two ways of knowing the weather.</p>
      <p id="d1e345">The first one is reflected in the ways in which the actual weather intrudes
on the senses, even when preference is given to scientific forecasts. I
experienced this myself when I was on a day trip with a field officer from a
local NGO at the beginning of the rainy season in 2018. After visiting
farmers, we were on a motorbike going back to a small market town on the
main highway where we would end the day. The morning had been clear and
sunny, but over the course of the day some clouds had been building up. By
then it was mid-afternoon, and we were going back on a dirt road. The field
officer looked back over his shoulder and pointed to the clouds that had
become larger and larger on the slopes of Mount Elgon. He urged the driver
to go faster so that we would reach our destination before the rain
started.<?pagebreak page94?> Eventually, however, he asked the driver to take a different route
and to go to a place where we could seek shelter. As the downpour started we
arrived on a large-scale farm where the officer knew one of the workers.
There, we spent the next 2 h in a grain storage, waiting for the rain
to subside (field notes, 16 March 2018).</p>
      <p id="d1e348">This experience shows that, even if one follows scientific forecasts as we
did, sometimes weather can come as a surprise. The state of the sky can
change quickly on timescales shorter than a forecast depicts. Similarly,
walking to a meeting with other farmers with Mary, she looked up at the sky
and said “today there'll be no rain”. I asked her how she knew and she
replied “because it's so hot” (field notes, 27 November 2017). Here, Mary
clearly used her own observations, despite receiving and using scientific
forecasts, which she had described earlier as a lot more accurate,
denouncing experiential knowledge as mere belief.</p>
      <p id="d1e351">A couple of days later, I sat in front of the house with her husband Isaac.
When I casually remarked that it is a windy day, he started explaining that
easterly winds are a sign of coming drought, that westerly winds from the
direction of Congo rather indicated rain, and that northerly and southerly
winds are a quite strong indication of rain. Only having said that, he added
that at least this was the imagination that people followed in earlier times
(field notes, 30 November 2017). While here he reaffirmed his doubt stated
earlier, it is clear that he still holds this knowledge. And the sincerity
with which he explained it, not having been specifically asked about it,
left an impression that it is still relevant to him.</p>
      <p id="d1e355">At a meeting with another farmer group in Trans Nzoia, one of the farmers
stated that he preferably uses expert forecasts. However, he then remarked
that the safari ants, which are said to be a traditional indication of
coming rain, bite regardless (field notes, 5 February 2018). This is an
interesting statement, because it shows that experiential proxies are
constantly present and make themselves recognized. In this case, they may
even bite. Therefore, while farmers may use expert predictions, they still
cannot ignore other proxies that stand in for the weather.</p>
      <p id="d1e358">As a second type of connection, farmers actively compare scientific
forecasts with their observations. This is the case when the farmer Joseph
told me that the current forecast predicts some rain. He added that he had
seen clouds, too, but that there had not been any rain yet. He later
explained that before he started to receive expert weather forecasts, he had
used what he called his own knowledge (field notes, 9 December 2017) and
apparently he still does: while he receives scientific forecasts, he also looks for the predicted rain by observing clouds. Here, he compares
what he sees with information he gets from meteorologists. Another farmer,
Malcolm, said that “you can see the weather and that the weather tells you
when to plant”. Nonetheless, the weather forecasts Mary forwards to him
“help because I can compare them with my own observations” (field notes,
8 December 2017). This farmer, as well, uses his own observation and
double-checks with expert forecasts.</p>
      <p id="d1e361">Such comparisons were not only made by farmers around Kakamega but also
common in Trans Nzoia. In a group discussion farmers explained their
observations of plants and animals in this way: “it is a kind of indigenous
knowledge. It supplements the weather forecast. What we see is that the
weather forecast says this, and the observation says the same. So it is
another indicator” (field notes, 7 November 2017).<?pagebreak page95?> Here, experiential
knowledge becomes yet another indication of rain in addition to the
scientific weather forecasts farmers receive. During a different time of the
year, the beginning of the of the rainy season (and hence the planting
season), I met Grace, a group leader who receives weather forecasts on her
phone, and her son Theodore. When I asked them how important the so-called
natural knowledge is compared to the weather forecasts during that season,
Grace replied that both are helpful. Theodore, in turn, added that the
forecasts are more accurate and explained that his mother had received the
forecasts, and that they have experienced what they said. He stated, “with
the leaves you cannot know what amount of rain will come or how long”
(interview, 17 March 2018). While this seems to be favoring scientific
forecasts, Theodore does not trust them blindly and still considers
observational signs for a comparison with expert forecasts. In other words,
even in judging the two ways of knowing weather and stating that the
scientific forecast is more useful, Theodore is acutely aware of the weather
through what he experiences and observes himself.</p>
      <p id="d1e364">Such comparative practices are not the same for each and every farmer. While
some emphasize scientific knowledge, others put more faith in their personal
experience and observations. On the one hand, Theodore puts a lot of trust
in scientific forecasts. The same applies to most members of one farmer
group who characterize the forecasts as accurate and useful since, “with
climate change, we are comparing it to indigenous knowledge but weather
becomes less predictable” (field notes, 7 November 2017), making experiential
observations more difficult to use.</p>
      <p id="d1e367">On the other hand, the farmers from Kakamega cited above stress their own
knowledge. Malcolm seems to predominantly use his own observations to
determine the time of planting and verifies them with scientific forecasts.
Joseph, too, receives weather forecasts but seems to wait until he can see
clear signs of rain before he acts on the information he gets both through
expert predictions and his observations. What is important for me here is
not to determine which one is actually more accurate and more trustworthy.
The point instead is that, in practice, farmers combine and compare several
ways of knowing the weather as a basis for making decisions. In farmers'
practices, then, no fundamental distinction is drawn between scientific and
experiential knowledge and both are important.</p>
      <p id="d1e370">A third type of entanglement can be identified when scientific and
experiential knowledge are combined differentially, i.e., by using different
kinds of information they provide. On the one hand, experiential knowledge
is predominantly used to determine points in time of the start and cessation
of rainfall events. In particular, it is used to estimate the beginning and
end of rainy seasons in order to know when to plant and to harvest,
respectively. On the other hand, the example of Grace and her son shows that
scientific forecasts provide additional information on the amounts and the
spatial distribution of rainfall. Farmers thus get a more fine-grained image
and make more detailed decisions on agricultural activities. Here, it is not
only crucial to know if and when rain is expected to fall but also whether
it is likely to be sufficient for planting.</p>
      <p id="d1e374">Of course, both modes of anticipating weather have a temporal dimension,
which means that they make statements about when things will happen and at
what time actions should be taken. As the examples of Mary and Joseph show,
however, farmers combine information from scientific forecasts and
experiential knowledge that pertains to differing temporal scales. Joseph
stated that he receives weekly weather forecasts from Mary, but in
continuously comparing this forecast with what he actually observes, he
combines the two sources of information in a way that he continuously checks
on what is happening in his environment. Here, he draws on weekly weather
forecasts, but in order to keep “up to date” with the weather throughout
the week Joseph uses his experiential skills of weather observation. A
similar observation can be made on a larger timescale, namely for the
beginnings and the ends of agricultural seasons. For example, approaching
the planting season, Mary stated, “We have to see the rain to plant. When
we get the forecast, it says it rains in A, B, C, but we might not get it
here. But you can prepare” (phone call, 8 March 2018). Farmers get
scientific forecasts well ahead of time and use these to prepare their
fields. Being aware of scientific forecasts' inherent uncertainties, when
the expected time of planting draws closer, they use their own observations
to make a decision to act.</p>
      <p id="d1e377">Farmers' use of both scientific and experiential knowledge generally
reflects earlier insights that rural populations draw on multiple sources of
and often mix indigenous and external information (Balehegn et al., 2019;
Vervoort et al., 2016). Adding to this, farmers' practices studied here show
how knowledges are combined in complex ways: on the one hand, with regards
to their temporal dimensions, scientific knowledge seems to be used more for
a general picture of what is going to happen, while experiential knowledge
then is used to determine specific points of time for actions to be taken.
On the other hand, when it comes to what kind of information they provide
the picture is reversed. Here, experiential knowledge tends to be used
predominantly to determine points of time, such as the beginning and
cessation of rainfalls. In turn, scientific knowledge, although coming with
uncertainties, too provides a wider array of additional information,
including the amounts and distributions of rain, which is also relevant
information for farmers and their decision-making.</p>
</sec>
<sec id="Ch1.S6" sec-type="conclusions">
  <label>6</label><title>Conclusions</title>
      <p id="d1e388">Knowing the weather is vital for small-scale farmers in Kenya, especially
under changing conditions which make farming more difficult. Against this
background, this paper set out with a critical engagement with<?pagebreak page96?> conventional
approaches to development that seek to solve those problems by focusing on
scientific knowledge and making it accessible to farmers through the use of
modern communication technologies. Instead, employing a perspective informed
by STS, I tackled problems of knowing the weather by recognizing the
multiplicity of knowledges at play among farmers in western Kenya and by
asking how knowledge about the weather is produced in scientific and
experiential practices, how these two forms can be understood more
symmetrically, and how they relate in farmers' everyday activities.</p>
      <p id="d1e391">Thinking forms of anticipating the weather particularly in terms of their
sensoria, proxies and imaginations allowed me to discuss the ways in which
they work symmetrically, which means to apply the same vocabulary to
describe their methods of observation and interpretation. While some
parallels between scientific and experiential knowledge have been identified
e.g., by Agrawal (1995), in the case explored here some aspects additionally
stand out: while the indirect and mediated character of scientific
measurement has been recognized, this is also the case in experiential
knowledge. Often assumed to rely on direct encounters with its objects of
knowledge, it partially depends on observing nonhuman sensoria and using
them as a proxy. In addition, the notion of “imagining” adequately
describes the context-dependent interpretative practices of both scientific
and experiential ways of weather forecasting. Considering how these forms of
knowledge relate in farmers' activities it became clear that these are not
separated but connected forms of knowing through which they attune to their
environment. While not necessarily in harmony with each other and some
farmers upheld essentialist distinctions with an explicit preference for
expert forecasts, in practice experiential and scientific knowledge appeared
far from opposed and were combined with regards to their respective contents
and temporal frames.</p>
      <p id="d1e394">This symmetry and hybridization of knowledge practices has important
implications for development projects that promote the dissemination and
application of scientific knowledge. Recognizing that all knowledge is
relational upsets universalist claims and means the “collapse of
[science's] distant gaze” (Ziebritzki, 2020: 263). Scientific knowledge
that projects that distant and global gaze then is not a solitary solution
to problems of change and uncertainty but one among many knowledge
practices. Here, certainty is not guaranteed by receiving and following
scientific knowledge alone, but it is derived from and honed through
practices that combine various ways of knowing environments. This profoundly
challenges modernist beliefs in technical fixes not uncommon in many
development projects adopting information technologies (Díaz Andrade
and Urquhart, 2012) by providing an example of how new knowledge does not take
over but rather folds into an existing context in unforeseen ways.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d1e401">In line with protecting individuals' personal data agreed on with research
participants, data are not publicly available.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e407">The author has declared that there are no competing interests.</p>
  </notes><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d1e413">Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
  </notes><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e419">This work was supported by a fellowship of the German Academic Exchange Service (DAAD) and by a grant of the German Research Foundation (DFG, grant no. TRR 228/1).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e425">This paper was edited by Myriam Houssay-Holzschuch and reviewed by two anonymous referees.</p>
  </notes><ref-list>
    <title>References</title>

      <ref id="bib1.bib1"><label>1</label><?label 1?><mixed-citation>Adams, B.: Digital Animals, The Philosopher, 108,
<uri>https://www.thephilosopher1923.org/adams</uri> (last access: 1 January 2023), 2020.</mixed-citation></ref>
      <ref id="bib1.bib2"><label>2</label><?label 1?><mixed-citation>Agrawal, A.: Dismantling the Divide Between Indigenous and Scientific
Knowledge, Dev. Cange, 26, 413–439,
<ext-link xlink:href="https://doi.org/10.1111/j.1467-7660.1995.tb00560.x" ext-link-type="DOI">10.1111/j.1467-7660.1995.tb00560.x</ext-link>, 1995.</mixed-citation></ref>
      <ref id="bib1.bib3"><label>3</label><?label 1?><mixed-citation>Balehegn, M., Balehey, S., Fu, C., and Liang, W.: Indigenous weather and
climate forecasting knowledge among Afar pastoralists of north eastern
Ethiopia: Role in adaptation to weather and climate variability,
Pastoralism, 9, 8, <ext-link xlink:href="https://doi.org/10.1186/s13570-019-0143-y" ext-link-type="DOI">10.1186/s13570-019-0143-y</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib4"><label>4</label><?label 1?><mixed-citation>Ballestero, A.: Touching with Light, or, How Texture Recasts the Sensing of Underground Water, Sci. Technol. Hum. Val., 44, 762–785,
<ext-link xlink:href="https://doi.org/10.1177/0162243919858717" ext-link-type="DOI">10.1177/0162243919858717</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib5"><label>5</label><?label 1?><mixed-citation>Bauriedl, S.: Politische Ökologie: nicht-deterministische, globale und materielle Dimensionen von Natur/Gesellschaft-Verhältnissen, Geogr. Helv., 71, 341–351, <ext-link xlink:href="https://doi.org/10.5194/gh-71-341-2016" ext-link-type="DOI">10.5194/gh-71-341-2016</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib6"><label>6</label><?label 1?><mixed-citation>
Caine, A., Clarke, C., Clarkson, G., and Dorward, P.: Mobile Phone
Applications for Weather and Climate Information for Smallholder Farmer
Decision Making, in: Digital technologies for agricultural and rural
development in the global south, edited by: Duncombe, R., CABI, Boston, MA, ISBN 9781786394804, 1–13, 2018.</mixed-citation></ref>
      <ref id="bib1.bib7"><label>7</label><?label 1?><mixed-citation>Calvillo, N.: Political airs: From monitoring to attuned sensing air
pollution, Soc. Stud. Sci., 48, 372–388,
<ext-link xlink:href="https://doi.org/10.1177/0306312718784656" ext-link-type="DOI">10.1177/0306312718784656</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib8"><label>8</label><?label 1?><mixed-citation>Coté, M.: Technics and the human sensorium: rethinking media theory
though the body, Theory &amp; Event, 13,
<uri>https://muse.jhu.edu/article/407142</uri> (last access: 1 January 2023), 2010.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib9"><label>9</label><?label 1?><mixed-citation>Despret, V.: The Body We Care for: Figures of Anthropo-zoo-genesis, Body Soc., 10, 111–134, <ext-link xlink:href="https://doi.org/10.1177/1357034X04042938" ext-link-type="DOI">10.1177/1357034X04042938</ext-link>, 2004.</mixed-citation></ref>
      <ref id="bib1.bib10"><label>10</label><?label 1?><mixed-citation>Díaz Andrade, A. and Urquhart, C.: Unveiling the modernity bias: A critical examination of the politics of ICT4D, Inform. Technol. Dev., 18, 281–292, <ext-link xlink:href="https://doi.org/10.1080/02681102.2011.643204" ext-link-type="DOI">10.1080/02681102.2011.643204</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib11"><label>11</label><?label 1?><mixed-citation>
Edwards, P. N.: Representing the Global Atmosphere: Computer Models, Data, and Knowledge about Climate Change, in: Changing the atmosphere: Expert knowledge and environmental governance, edited by: Miller, C. A. and Edwards, P. N., MIT Press, Cambridge, Mass, 31–65, ISBN 9780262632195, 2001.</mixed-citation></ref>
      <ref id="bib1.bib12"><label>12</label><?label 1?><mixed-citation>FAO: Crop Calendar,
<uri>https://cropcalendar.apps.fao.org/#/home?id=KE&amp;crops=0113</uri> (last
access: 1 July 2022), 2021.</mixed-citation></ref>
      <ref id="bib1.bib13"><label>13</label><?label 1?><mixed-citation>Gabrys, J.: Sensors and Sensing Practices: Reworking Experience across
Entities, Environments, and Technologies, Sci. Technol. Hum. Val., 44, 723–736, <ext-link xlink:href="https://doi.org/10.1177/0162243919860211" ext-link-type="DOI">10.1177/0162243919860211</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib14"><label>14</label><?label 1?><mixed-citation>Gabrys, J.: Practicing, materialising and contesting environmental data, Big Data &amp; Society, 3, 1–7, <ext-link xlink:href="https://doi.org/10.1177/2053951716673391" ext-link-type="DOI">10.1177/2053951716673391</ext-link>, 2016a.</mixed-citation></ref>
      <ref id="bib1.bib15"><label>15</label><?label 1?><mixed-citation>
Gabrys, J.: Program earth: Environmental sensing technology and the making
of a computational planet, Electronic mediations, 49, University of
Minnesota Press, Minneapolis, 357 pp., ISBN 978-0-8166-9312-2, 2016b.</mixed-citation></ref>
      <ref id="bib1.bib16"><label>16</label><?label 1?><mixed-citation>
Goldman, M. and Turner, M. D.: Introduction, in: Knowing nature:
Conversations at the Intersection of political ecology and science studies,
edited by: Goldman, M., Turner, M. D., and Nadasdy, P., University of
Chicago Press, Chicago, London, 1–23, ISBN 9780226301402, 2011.</mixed-citation></ref>
      <ref id="bib1.bib17"><label>17</label><?label 1?><mixed-citation>Government of Kenya: National Climate Change Response Strategy,
<uri>https://cdkn.org/sites/default/files/files/National-Climate-Change-Response-Strategy_April-2010.pdf</uri> (last access: 14 June 2022), 2010.</mixed-citation></ref>
      <ref id="bib1.bib18"><label>18</label><?label 1?><mixed-citation>Gumo, S.: Praying for Rain: Indigenous Systems of Rainmaking in Kenya, Ecumenical Rev., 69, 386–397, <ext-link xlink:href="https://doi.org/10.1111/erev.12301" ext-link-type="DOI">10.1111/erev.12301</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib19"><label>19</label><?label 1?><mixed-citation>Hannerz, U.: Being there<inline-formula><mml:math id="M4" display="inline"><mml:mi mathvariant="normal">…</mml:mi></mml:math></inline-formula> and there<inline-formula><mml:math id="M5" display="inline"><mml:mi mathvariant="normal">…</mml:mi></mml:math></inline-formula> and there!:
Reflections on multi-site ethnography, Ethnography, 4, 201–216, 2003.</mixed-citation></ref>
      <ref id="bib1.bib20"><label>20</label><?label 1?><mixed-citation>
Harper, K.: Weather by the numbers: The genesis of modern meteorology,
Transformations, MIT Press, Cambridge, Mass., 308 pp., ISBN 978-0-262-08378-2, 2008.</mixed-citation></ref>
      <ref id="bib1.bib21"><label>21</label><?label 1?><mixed-citation>Howe, C.: Sensing Asymmetries in Other-than-human Forms, Sci. Technol. Hum. Val., 44, 900–910, <ext-link xlink:href="https://doi.org/10.1177/0162243919852675" ext-link-type="DOI">10.1177/0162243919852675</ext-link>,
2019.</mixed-citation></ref>
      <ref id="bib1.bib22"><label>22</label><?label 1?><mixed-citation>Iticha, B. and Husen, A.: Adaptation to climate change using indigenous
weather forecasting systems in Borana pastoralists of southern Ethiopia,
Climate and Development, 11, 564–573,
<ext-link xlink:href="https://doi.org/10.1080/17565529.2018.1507896" ext-link-type="DOI">10.1080/17565529.2018.1507896</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib23"><label>23</label><?label 1?><mixed-citation>Jansen, K. and Vellema, S.: What is technography?, NJAS-Wagen. J. Life Sc., 57, 169–177, <ext-link xlink:href="https://doi.org/10.1016/j.njas.2010.11.003" ext-link-type="DOI">10.1016/j.njas.2010.11.003</ext-link>,
2011.</mixed-citation></ref>
      <ref id="bib1.bib24"><label>24</label><?label 1?><mixed-citation>Kien, G.: Technography <inline-formula><mml:math id="M6" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> Technology <inline-formula><mml:math id="M7" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> Ethnography, Qual. Inq.,
14, 1101–1109, <ext-link xlink:href="https://doi.org/10.1177/1077800408318433" ext-link-type="DOI">10.1177/1077800408318433</ext-link>, 2008.</mixed-citation></ref>
      <ref id="bib1.bib25"><label>25</label><?label 1?><mixed-citation>Latour, B.: Agency at the Time of the Anthropocene, New Literary History,
45, 1–18, <ext-link xlink:href="https://doi.org/10.1353/nlh.2014.0003" ext-link-type="DOI">10.1353/nlh.2014.0003</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib26"><label>26</label><?label 1?><mixed-citation>
Latour, B.: An inquiry into modes of existence: An anthropology of the
moderns, Harvard Univ. Press, Cambridge, Mass., 486 pp., ISBN 9780674724990, 2013.</mixed-citation></ref>
      <ref id="bib1.bib27"><label>27</label><?label 1?><mixed-citation>
Latour, B.: Reassembling the social: An introduction to
Actor-Network-Theory, Clarendon lectures in management studies, Oxford Univ.
Press, Oxford, 301 pp., ISBN 9780199256051, 2007.</mixed-citation></ref>
      <ref id="bib1.bib28"><label>28</label><?label 1?><mixed-citation>
Latour, B.: We have never been modern, Harvard Univ. Press, Cambridge, Mass,
157 pp., ISBN 0-674-94839-4, 1993.</mixed-citation></ref>
      <ref id="bib1.bib29"><label>29</label><?label 1?><mixed-citation>
Latour, B.: Science in action: How to follow scientists and engineers
through society, Harvard Univ. Press, Cambridge, Mass., 274 pp., ISBN 0674792912, 1987.</mixed-citation></ref>
      <ref id="bib1.bib30"><label>30</label><?label 1?><mixed-citation>
Law, J.: Modes of knowing: Resources from the Baroque, in: Modes of knowing:
Resources from the Baroque, First edition, edited by: Law, J. and Ruppert,
E., Mattering Press, Manchester, 17–57, ISBN 978-0-9931449-9-8, 2016.</mixed-citation></ref>
      <ref id="bib1.bib31"><label>31</label><?label 1?><mixed-citation>
Morton, T.: Being Ecological, MIT Press, Cambridge, Mass., ISBN 9780262537124, 2018.</mixed-citation></ref>
      <ref id="bib1.bib32"><label>32</label><?label 1?><mixed-citation>Nyadzi, E., Werners, S. E., Biesbroek, R., and Ludwig, F.: Techniques and
skills of indigenous weather and seasonal climate forecast in Northern
Ghana, Clim. Dev., 13, 551–562,
<ext-link xlink:href="https://doi.org/10.1080/17565529.2020.1831429" ext-link-type="DOI">10.1080/17565529.2020.1831429</ext-link>, 2021.</mixed-citation></ref>
      <ref id="bib1.bib33"><label>33</label><?label 1?><mixed-citation>Orlove, B., Roncoli, C., Kabugo, M., and Majugu, A.: Indigenous climate
knowledge in southern Uganda: the multiple components of a dynamic regional
system, Climatic Change, 100, 243–265,
<ext-link xlink:href="https://doi.org/10.1007/s10584-009-9586-2" ext-link-type="DOI">10.1007/s10584-009-9586-2</ext-link>, 2010.</mixed-citation></ref>
      <ref id="bib1.bib34"><label>34</label><?label 1?><mixed-citation>
Ouma, G., Laban, O., and Onyango, M.: Coping with local disasters using
indigenous knowledge: Experiences from Nganyi community of Western Kenya,
LAP LAMBERT Academic Publishing, Saarbrücken, 112 pp., ISBN 9783659451010, 2013.</mixed-citation></ref>
      <ref id="bib1.bib35"><label>35</label><?label 1?><mixed-citation>Rice, J. L., Burke, B. J., and Heynen, N.: Knowing Climate Change, Embodying
Climate Praxis: Experiential Knowledge in Southern Appalachia,
Ann. Assoc. Am. Geogr., 105, 253–262,
<ext-link xlink:href="https://doi.org/10.1080/00045608.2014.985628" ext-link-type="DOI">10.1080/00045608.2014.985628</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib36"><label>36</label><?label 1?><mixed-citation>Taylor, J.: The Complete Weather Guide: A Collection of Practical
Observations for Prognosticating the Weather, Drawn from Plants, Animals,
Inanimate Bodies, and Also by Means of Philosophical Instruments, Cambridge
library collection. Earth sciences, Cambridge University Press, Cambridge,
160 pp., <ext-link xlink:href="https://doi.org/10.1017/CBO9781107323841" ext-link-type="DOI">10.1017/CBO9781107323841</ext-link>, 2013 [1812].</mixed-citation></ref>
      <ref id="bib1.bib37"><label>37</label><?label 1?><mixed-citation>
Tsing, A. L.: Interview with Anna Tsing, Suomen Antropologi, 42, 22–30,
2017.</mixed-citation></ref>
      <ref id="bib1.bib38"><label>38</label><?label 1?><mixed-citation>
Tsing, A. L.: The mushroom at the end of the world: On the possibility of
life in capitalist ruins, Princeton University Press, Princeton, xii, 331 pp., ISBN 9780691162751, 2015.</mixed-citation></ref>
      <ref id="bib1.bib39"><label>39</label><?label 1?><mixed-citation>Vervoort, R. W., Muita, R., Ampt, P., and van Ogtrop, F.: Managing the water
cycle in Kenyan small-scale maize farming systems: Part 2. Farmers' use of
formal and informal climate forecasts, WIREs Water, 3, 127–140,
<ext-link xlink:href="https://doi.org/10.1002/wat2.1121" ext-link-type="DOI">10.1002/wat2.1121</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib40"><label>40</label><?label 1?><mixed-citation>Watts, N. and Scales, I. R.: Seeds, Agricultural Systems and Socio-natures:
Towards an Actor-Network Theory Informed Political Ecology of Agriculture,
Geography Compass, 9, 225–236, <ext-link xlink:href="https://doi.org/10.1111/gec3.12212" ext-link-type="DOI">10.1111/gec3.12212</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib41"><label>41</label><?label 1?><mixed-citation>Whatmore, S.: Political Ecology in a More-than-Human World: Rethinking
“Natural” Hazards, in: Anthropology and nature, edited by: Hastrup, K.,
Routledge Taylor &amp; Francis Group, New York, London, 79–95, ISBN 978-0-203-79536-1, 2014.
 </mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib42"><label>42</label><?label 1?><mixed-citation>Whatmore, S.: Hybrid geographies: Natures, cultures, spaces, Reprint, SAGE,
London, 225 pp., ISBN 0761965661, 2006.
 </mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib43"><label>43</label><?label 1?><mixed-citation>Ziebritzki, J.: Sensorium of the Earthbound, in: Critical zones: The science
and politics of landing on earth, edited by: Latour, B. and Weibel, P., ZKM <inline-formula><mml:math id="M8" display="inline"><mml:mo>|</mml:mo></mml:math></inline-formula> Center for Art and Media Karlsruhe Germany; The MIT Press,
Karlsruhe, Cambridge, MA, London, England, 260–263, ISBN 9780262044455, 2020.</mixed-citation></ref>

  </ref-list></back>
    <!--<article-title-html>Sensing weather: scientific and experiential modes of knowledge production for small-scale  farming in western Kenya</article-title-html>
<abstract-html/>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
      
Adams, B.: Digital Animals, The Philosopher, 108,
<a href="https://www.thephilosopher1923.org/adams" target="_blank"/> (last access: 1 January 2023), 2020.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
      
Agrawal, A.: Dismantling the Divide Between Indigenous and Scientific
Knowledge, Dev. Cange, 26, 413–439,
<a href="https://doi.org/10.1111/j.1467-7660.1995.tb00560.x" target="_blank">https://doi.org/10.1111/j.1467-7660.1995.tb00560.x</a>, 1995.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
      
Balehegn, M., Balehey, S., Fu, C., and Liang, W.: Indigenous weather and
climate forecasting knowledge among Afar pastoralists of north eastern
Ethiopia: Role in adaptation to weather and climate variability,
Pastoralism, 9, 8, <a href="https://doi.org/10.1186/s13570-019-0143-y" target="_blank">https://doi.org/10.1186/s13570-019-0143-y</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
      
Ballestero, A.: Touching with Light, or, How Texture Recasts the Sensing of Underground Water, Sci. Technol. Hum. Val., 44, 762–785,
<a href="https://doi.org/10.1177/0162243919858717" target="_blank">https://doi.org/10.1177/0162243919858717</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
      
Bauriedl, S.: Politische Ökologie: nicht-deterministische, globale und materielle Dimensionen von Natur/Gesellschaft-Verhältnissen, Geogr. Helv., 71, 341–351, <a href="https://doi.org/10.5194/gh-71-341-2016" target="_blank">https://doi.org/10.5194/gh-71-341-2016</a>, 2016.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
      
Caine, A., Clarke, C., Clarkson, G., and Dorward, P.: Mobile Phone
Applications for Weather and Climate Information for Smallholder Farmer
Decision Making, in: Digital technologies for agricultural and rural
development in the global south, edited by: Duncombe, R., CABI, Boston, MA, ISBN 9781786394804, 1–13, 2018.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
      
Calvillo, N.: Political airs: From monitoring to attuned sensing air
pollution, Soc. Stud. Sci., 48, 372–388,
<a href="https://doi.org/10.1177/0306312718784656" target="_blank">https://doi.org/10.1177/0306312718784656</a>, 2018.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
      
Coté, M.: Technics and the human sensorium: rethinking media theory
though the body, Theory &amp; Event, 13,
<a href="https://muse.jhu.edu/article/407142" target="_blank"/> (last access: 1 January 2023), 2010.


    </mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
      
Despret, V.: The Body We Care for: Figures of Anthropo-zoo-genesis, Body Soc., 10, 111–134, <a href="https://doi.org/10.1177/1357034X04042938" target="_blank">https://doi.org/10.1177/1357034X04042938</a>, 2004.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
      
Díaz Andrade, A. and Urquhart, C.: Unveiling the modernity bias: A critical examination of the politics of ICT4D, Inform. Technol. Dev., 18, 281–292, <a href="https://doi.org/10.1080/02681102.2011.643204" target="_blank">https://doi.org/10.1080/02681102.2011.643204</a>, 2012.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>11</label><mixed-citation>
      
Edwards, P. N.: Representing the Global Atmosphere: Computer Models, Data, and Knowledge about Climate Change, in: Changing the atmosphere: Expert knowledge and environmental governance, edited by: Miller, C. A. and Edwards, P. N., MIT Press, Cambridge, Mass, 31–65, ISBN 9780262632195, 2001.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>12</label><mixed-citation>
      
FAO: Crop Calendar,
<a href="https://cropcalendar.apps.fao.org/#/home?id=KE&amp;crops=0113" target="_blank"/> (last
access: 1 July 2022), 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>13</label><mixed-citation>
      
Gabrys, J.: Sensors and Sensing Practices: Reworking Experience across
Entities, Environments, and Technologies, Sci. Technol. Hum. Val., 44, 723–736, <a href="https://doi.org/10.1177/0162243919860211" target="_blank">https://doi.org/10.1177/0162243919860211</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib14"><label>14</label><mixed-citation>
      
Gabrys, J.: Practicing, materialising and contesting environmental data, Big Data &amp; Society, 3, 1–7, <a href="https://doi.org/10.1177/2053951716673391" target="_blank">https://doi.org/10.1177/2053951716673391</a>, 2016a.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib15"><label>15</label><mixed-citation>
      
Gabrys, J.: Program earth: Environmental sensing technology and the making
of a computational planet, Electronic mediations, 49, University of
Minnesota Press, Minneapolis, 357 pp., ISBN 978-0-8166-9312-2, 2016b.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib16"><label>16</label><mixed-citation>
      
Goldman, M. and Turner, M. D.: Introduction, in: Knowing nature:
Conversations at the Intersection of political ecology and science studies,
edited by: Goldman, M., Turner, M. D., and Nadasdy, P., University of
Chicago Press, Chicago, London, 1–23, ISBN 9780226301402, 2011.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib17"><label>17</label><mixed-citation>
      
Government of Kenya: National Climate Change Response Strategy,
<a href="https://cdkn.org/sites/default/files/files/National-Climate-Change-Response-Strategy_April-2010.pdf" target="_blank"/> (last access: 14 June 2022), 2010.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib18"><label>18</label><mixed-citation>
      
Gumo, S.: Praying for Rain: Indigenous Systems of Rainmaking in Kenya, Ecumenical Rev., 69, 386–397, <a href="https://doi.org/10.1111/erev.12301" target="_blank">https://doi.org/10.1111/erev.12301</a>, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib19"><label>19</label><mixed-citation>
      
Hannerz, U.: Being there… and there… and there!:
Reflections on multi-site ethnography, Ethnography, 4, 201–216, 2003.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib20"><label>20</label><mixed-citation>
      
Harper, K.: Weather by the numbers: The genesis of modern meteorology,
Transformations, MIT Press, Cambridge, Mass., 308 pp., ISBN 978-0-262-08378-2, 2008.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib21"><label>21</label><mixed-citation>
      
Howe, C.: Sensing Asymmetries in Other-than-human Forms, Sci. Technol. Hum. Val., 44, 900–910, <a href="https://doi.org/10.1177/0162243919852675" target="_blank">https://doi.org/10.1177/0162243919852675</a>,
2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib22"><label>22</label><mixed-citation>
      
Iticha, B. and Husen, A.: Adaptation to climate change using indigenous
weather forecasting systems in Borana pastoralists of southern Ethiopia,
Climate and Development, 11, 564–573,
<a href="https://doi.org/10.1080/17565529.2018.1507896" target="_blank">https://doi.org/10.1080/17565529.2018.1507896</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib23"><label>23</label><mixed-citation>
      
Jansen, K. and Vellema, S.: What is technography?, NJAS-Wagen. J. Life Sc., 57, 169–177, <a href="https://doi.org/10.1016/j.njas.2010.11.003" target="_blank">https://doi.org/10.1016/j.njas.2010.11.003</a>,
2011.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib24"><label>24</label><mixed-citation>
      
Kien, G.: Technography&thinsp; = &thinsp;Technology&thinsp;+&thinsp;Ethnography, Qual. Inq.,
14, 1101–1109, <a href="https://doi.org/10.1177/1077800408318433" target="_blank">https://doi.org/10.1177/1077800408318433</a>, 2008.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib25"><label>25</label><mixed-citation>
      
Latour, B.: Agency at the Time of the Anthropocene, New Literary History,
45, 1–18, <a href="https://doi.org/10.1353/nlh.2014.0003" target="_blank">https://doi.org/10.1353/nlh.2014.0003</a>, 2014.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib26"><label>26</label><mixed-citation>
      
Latour, B.: An inquiry into modes of existence: An anthropology of the
moderns, Harvard Univ. Press, Cambridge, Mass., 486 pp., ISBN 9780674724990, 2013.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib27"><label>27</label><mixed-citation>
      
Latour, B.: Reassembling the social: An introduction to
Actor-Network-Theory, Clarendon lectures in management studies, Oxford Univ.
Press, Oxford, 301 pp., ISBN 9780199256051, 2007.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib28"><label>28</label><mixed-citation>
      
Latour, B.: We have never been modern, Harvard Univ. Press, Cambridge, Mass,
157 pp., ISBN 0-674-94839-4, 1993.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib29"><label>29</label><mixed-citation>
      
Latour, B.: Science in action: How to follow scientists and engineers
through society, Harvard Univ. Press, Cambridge, Mass., 274 pp., ISBN 0674792912, 1987.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib30"><label>30</label><mixed-citation>
      
Law, J.: Modes of knowing: Resources from the Baroque, in: Modes of knowing:
Resources from the Baroque, First edition, edited by: Law, J. and Ruppert,
E., Mattering Press, Manchester, 17–57, ISBN 978-0-9931449-9-8, 2016.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib31"><label>31</label><mixed-citation>
      
Morton, T.: Being Ecological, MIT Press, Cambridge, Mass., ISBN 9780262537124, 2018.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib32"><label>32</label><mixed-citation>
      
Nyadzi, E., Werners, S. E., Biesbroek, R., and Ludwig, F.: Techniques and
skills of indigenous weather and seasonal climate forecast in Northern
Ghana, Clim. Dev., 13, 551–562,
<a href="https://doi.org/10.1080/17565529.2020.1831429" target="_blank">https://doi.org/10.1080/17565529.2020.1831429</a>, 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib33"><label>33</label><mixed-citation>
      
Orlove, B., Roncoli, C., Kabugo, M., and Majugu, A.: Indigenous climate
knowledge in southern Uganda: the multiple components of a dynamic regional
system, Climatic Change, 100, 243–265,
<a href="https://doi.org/10.1007/s10584-009-9586-2" target="_blank">https://doi.org/10.1007/s10584-009-9586-2</a>, 2010.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib34"><label>34</label><mixed-citation>
      
Ouma, G., Laban, O., and Onyango, M.: Coping with local disasters using
indigenous knowledge: Experiences from Nganyi community of Western Kenya,
LAP LAMBERT Academic Publishing, Saarbrücken, 112 pp., ISBN 9783659451010, 2013.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib35"><label>35</label><mixed-citation>
      
Rice, J. L., Burke, B. J., and Heynen, N.: Knowing Climate Change, Embodying
Climate Praxis: Experiential Knowledge in Southern Appalachia,
Ann. Assoc. Am. Geogr., 105, 253–262,
<a href="https://doi.org/10.1080/00045608.2014.985628" target="_blank">https://doi.org/10.1080/00045608.2014.985628</a>, 2015.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib36"><label>36</label><mixed-citation>
      
Taylor, J.: The Complete Weather Guide: A Collection of Practical
Observations for Prognosticating the Weather, Drawn from Plants, Animals,
Inanimate Bodies, and Also by Means of Philosophical Instruments, Cambridge
library collection. Earth sciences, Cambridge University Press, Cambridge,
160 pp., <a href="https://doi.org/10.1017/CBO9781107323841" target="_blank">https://doi.org/10.1017/CBO9781107323841</a>, 2013 [1812].

    </mixed-citation></ref-html>
<ref-html id="bib1.bib37"><label>37</label><mixed-citation>
      
Tsing, A. L.: Interview with Anna Tsing, Suomen Antropologi, 42, 22–30,
2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib38"><label>38</label><mixed-citation>
      
Tsing, A. L.: The mushroom at the end of the world: On the possibility of
life in capitalist ruins, Princeton University Press, Princeton, xii, 331 pp., ISBN 9780691162751, 2015.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib39"><label>39</label><mixed-citation>
      
Vervoort, R. W., Muita, R., Ampt, P., and van Ogtrop, F.: Managing the water
cycle in Kenyan small-scale maize farming systems: Part 2. Farmers' use of
formal and informal climate forecasts, WIREs Water, 3, 127–140,
<a href="https://doi.org/10.1002/wat2.1121" target="_blank">https://doi.org/10.1002/wat2.1121</a>, 2016.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib40"><label>40</label><mixed-citation>
      
Watts, N. and Scales, I. R.: Seeds, Agricultural Systems and Socio-natures:
Towards an Actor-Network Theory Informed Political Ecology of Agriculture,
Geography Compass, 9, 225–236, <a href="https://doi.org/10.1111/gec3.12212" target="_blank">https://doi.org/10.1111/gec3.12212</a>, 2015.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib41"><label>41</label><mixed-citation>
      
Whatmore, S.: Political Ecology in a More-than-Human World: Rethinking
“Natural” Hazards, in: Anthropology and nature, edited by: Hastrup, K.,
Routledge Taylor &amp; Francis Group, New York, London, 79–95, ISBN 978-0-203-79536-1, 2014.


    </mixed-citation></ref-html>
<ref-html id="bib1.bib42"><label>42</label><mixed-citation>
      
Whatmore, S.: Hybrid geographies: Natures, cultures, spaces, Reprint, SAGE,
London, 225 pp., ISBN 0761965661, 2006.


    </mixed-citation></ref-html>
<ref-html id="bib1.bib43"><label>43</label><mixed-citation>
      
Ziebritzki, J.: Sensorium of the Earthbound, in: Critical zones: The science
and politics of landing on earth, edited by: Latour, B. and Weibel, P., ZKM | Center for Art and Media Karlsruhe Germany; The MIT Press,
Karlsruhe, Cambridge, MA, London, England, 260–263, ISBN 9780262044455, 2020.

    </mixed-citation></ref-html>--></article>
